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ORCIDStan Matwin
2020 – today
- 2025
[j85]Jianzhe Zhao, Wenji Wang, Jiabao Wang, Songyang Zhang, Zhelin Fan, Stan Matwin:
Privacy-preserved federated clustering with Non-IID data via GANs. J. Supercomput. 81(4): 512 (2025)- 2024
- [j84]Hamed Jelodar, Rita Orji, Stan Matwin, Swarna Weerasinghe, Oladapo Oyebode, Yongli Wang:
Correction to: Emotion detection and semantic trends during COVID-19 social isolation using artificial intelligence techniques. J. Ambient Intell. Humaniz. Comput. 15(4): 2653 (2024) - [j83]Will Taylor-Melanson, Zahra Sadeghi, Stan Matwin:
Causal generative explainers using counterfactual inference: a case study on the Morpho-MNIST dataset. Pattern Anal. Appl. 27(3): 89 (2024) - [j82]Gabriel Spadon
, Jay Kumar, Jinkun Chen, Matthew Smith, Casey Hilliard, Sarah Vela, Romina Gehrmann, Claudio DiBacco, Stan Matwin, Ronald Pelot:
Maritime tracking data analysis and integration with AISdb. SoftwareX 28: 101952 (2024) - [j81]Martha Dais Ferreira, Zahra Sadeghi, Stan Matwin:
Exploring autoregression patterns for automatic vessel type classification. J. Supercomput. 80(7): 9532-9553 (2024) - [c218]Zahra Sadeghi, Stan Matwin:
A Computationally Inexpensive Method for Anomaly Detection in Maritime Trajectories from AIS Dataset. FICC (3) 2024: 304-317 - [i51]Nader Zare, Omid Amini, Aref Sayareh, Mahtab Sarvmaili, Arad Firouzkouhi, Stan Matwin, Amílcar Soares:
Improving Dribbling, Passing, and Marking Actions in Soccer Simulation 2D Games Using Machine Learning. CoRR abs/2401.03406 (2024) - [i50]Nader Zare, Mahtab Sarvmaili, Aref Sayareh, Omid Amini, Stan Matwin, Amílcar Soares:
Engineering Features to Improve Pass Prediction in Soccer Simulation 2D Games. CoRR abs/2401.03410 (2024) - [i49]Will Taylor-Melanson, Zahra Sadeghi, Stan Matwin:
Causal Generative Explainers using Counterfactual Inference: A Case Study on the Morpho-MNIST Dataset. CoRR abs/2401.11394 (2024) - [i48]Ruixin Song, Gabriel Spadon, Ronald Pelot, Stan Matwin, Amílcar Soares:
Gravity-Informed Deep Learning Framework for Predicting Ship Traffic Flow and Invasion Risk of Non-Indigenous Species via Ballast Water Discharge. CoRR abs/2401.13098 (2024) - [i47]Zahra Sadeghi, Stan Matwin:
A Review of Global Sensitivity Analysis Methods and a comparative case study on Digit Classification. CoRR abs/2406.16975 (2024) - [i46]Gabriel Spadon, Jay Kumar, Jinkun Chen, Matthew Smith, Casey Hilliard, Sarah Vela, Romina Gehrmann, Claudio DiBacco, Stan Matwin, Ronald Pelot:
Maritime Tracking Data Analysis and Integration with AISdb. CoRR abs/2407.08082 (2024) - 2023
- [b1]Stan Matwin, Aristides Milios, Pawel Pralat, Amílcar Soares, François Théberge:
Generative Methods for Social Media Analysis. Springer Briefs in Computer Science, Springer 2023, ISBN 978-3-031-33616-4, pp. 1-67 - [j80]Noah Barrett, Zahra Sadeghi, Stan Matwin:
Evolutionary Augmentation Policy Optimization for Self-Supervised Learning. Adv. Artif. Intell. Mach. Learn. 3(2): 1135-1164 (2023) - [j79]Gabriel Spadon, Martha Dais Ferreira, Amílcar Soares, Stan Matwin:
Unfolding AIS Transmission Behavior for Vessel Movement Modeling on Noisy Data Leveraging Machine Learning. IEEE Access 11: 18821-18837 (2023) - [j78]Audrey Looby, Sarah Vela, Kieran Cox, Amalis Riera, Santiago Bravo, Hailey L. Davies, Rodney Rountree, Laura K. Reynolds, Charles W. Martin, Stan Matwin, Francis Juanes:
FishSounds Version 1.0: A website for the compilation of fish sound production information and recordings. Ecol. Informatics 74: 101953 (2023) - [j77]Bruno Padovese, Oliver S. Kirsebom, Fábio Frazão, Clair H. M. Evers, Wilfried A. M. Beslin, Jim Theriault, Stan Matwin:
Adapting deep learning models to new acoustic environments - A case study on the North Atlantic right whale upcall. Ecol. Informatics 77: 102169 (2023) - [j76]Martha Dais Ferreira, Jessica N. A. Campbell, Evan Purney, Amílcar Soares, Stan Matwin:
Assessing compression algorithms to improve the efficiency of clustering analysis on AIS vessel trajectories. Int. J. Geogr. Inf. Sci. 37(3): 660-683 (2023) - [j75]Zahra Sadeghi, Stan Matwin:
Anomaly detection for maritime navigation based on probability density function of error of reconstruction. J. Intell. Syst. 32(1) (2023) - [j74]Will Taylor-Melanson, Martha Dais Ferreira, Stan Matwin:
SGORNN: Combining scalar gates and orthogonal constraints in recurrent networks. Neural Networks 159: 25-33 (2023) - [j73]Jianzhe Zhao, Chenxi Huang, Wenji Wang, Rulin Xie, Rongrong Dong, Stan Matwin:
Local differentially private federated learning with homomorphic encryption. J. Supercomput. 79(17): 19365-19395 (2023) - [c217]Lubna Eljabu, Mohammad Etemad, Stan Matwin:
Charting the Course of Ship Track Prediction: A Novel Approach for Maritime Traffic Analysis and Enhanced Situational Awareness. IEEE Big Data 2023: 2588-2597 - [i45]Noah Barrett, Zahra Sadeghi, Stan Matwin:
Evolutionary Augmentation Policy Optimization for Self-supervised Learning. CoRR abs/2303.01584 (2023) - [i44]Aref Sayareh, Nader Zare, Omid Amini, Arad Firouzkouhi, Mahtab Sarvmaili, Stan Matwin:
Observation Denoising in CYRUS Soccer Simulation 2D Team For RoboCup 2023. CoRR abs/2305.19283 (2023) - [i43]Nader Zare, Aref Sayareh, Omid Amini, Mahtab Sarvmaili, Arad Firouzkouhi, Stan Matwin, Amílcar Soares:
Pyrus Base: An Open Source Python Framework for the RoboCup 2D Soccer Simulation. CoRR abs/2307.16875 (2023) - [i42]Gabriel Spadon, Jay Kumar, Matthew Smith, Sarah Vela, Romina Gehrmann, Derek Eden, Joshua van Berkel, Amílcar Soares, Ronan Fablet, Ronald Pelot, Stan Matwin:
Building a Safer Maritime Environment Through Multi-Path Long-Term Vessel Trajectory Forecasting. CoRR abs/2310.18948 (2023) - 2022
- [j72]Ahmad Pesaranghader, Stan Matwin, Marina Sokolova, Jean-Christophe Grenier, Robert G. Beiko, Julie Hussin:
deepSimDEF: deep neural embeddings of gene products and gene ontology terms for functional analysis of genes. Bioinform. 38(11): 3051-3061 (2022) - [j71]Emanuele Carlini, Vinicius Monteiro de Lira, Amílcar Soares, Mohammad Etemad, Bruno Brandoli, Stan Matwin:
Understanding evolution of maritime networks from automatic identification system data. GeoInformatica 26(3): 479-503 (2022) - [j70]Bruno Brandoli, Alessandra Raffaetà, Marta Simeoni, Pedram Adibi, Fateha Khanam Bappee, Fabio Pranovi, Giulia Rovinelli, Elisabetta Russo, Claudio Silvestri, Amílcar Soares, Stan Matwin:
From multiple aspect trajectories to predictive analysis: a case study on fishing vessels in the Northern Adriatic sea. GeoInformatica 26(4): 551-579 (2022) - [j69]Oladapo Oyebode, Chinenye Ndulue, Dinesh Mulchandani, Banuchitra Suruliraj, Ashfaq Adib, Fidelia Anulika Orji, Evangelos E. Milios, Stan Matwin, Rita Orji:
COVID-19 Pandemic: Identifying Key Issues Using Social Media and Natural Language Processing. J. Heal. Informatics Res. 6(2): 174-207 (2022) - [j68]Gabriel Spadon, Shenda Hong, Bruno Brandoli, Stan Matwin, José F. Rodrigues Jr., Jimeng Sun:
Pay Attention to Evolution: Time Series Forecasting With Deep Graph-Evolution Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44(9): 5368-5384 (2022) - [j67]Martha Dais Ferreira, Gabriel Spadon, Amílcar Soares, Stan Matwin:
A Semi-Supervised Methodology for Fishing Activity Detection Using the Geometry behind the Trajectory of Multiple Vessels. Sensors 22(16): 6063 (2022) - [c216]Mahtab Sarvmaili, Riccardo Guidotti, Anna Monreale, Amílcar Soares, Zahra Sadeghi, Fosca Giannotti, Dino Pedreschi, Stan Matwin:
A Modularized Framework for Explaining Black Box Classifiers for Text Data. Canadian AI 2022 - [c215]Lubna Eljabu, Mohammad Etemad, Stan Matwin:
Spatial Clustering Method of Historical AIS Data for Maritime Traffic Routes Extraction. IEEE Big Data 2022: 893-902 - [c214]Farshid Varno, Marzie Saghayi, Laya Rafiee Sevyeri, Sharut Gupta, Stan Matwin, Mohammad Havaei:
AdaBest: Minimizing Client Drift in Federated Learning via Adaptive Bias Estimation. ECCV (23) 2022: 710-726 - [c213]Nader Zare, Omid Amini, Aref Sayareh, Mahtab Sarvmaili, Arad Firouzkouhi, Saba Ramezani Rad, Stan Matwin, Amílcar Soares:
Cyrus2D Base: Source Code Base for RoboCup 2D Soccer Simulation League. RoboCup 2022: 140-151 - [c212]Emanuele Carlini, Vinicius Monteiro de Lira, Amílcar Soares, Mohammad Etemad, Bruno Brandoli, Stan Matwin:
A Topological Perspective of Port Networks From Three Years (2017-2019) of AIS Data. SEBD 2022: 268-275 - [i41]Gabriel Spadon, Martha Dais Ferreira, Amílcar Soares, Stan Matwin:
Unfolding collective AIS transmission behavior for vessel movement modeling on irregular timing data using noise-robust neural networks. CoRR abs/2202.13867 (2022) - [i40]Farshid Varno, Marzie Saghayi, Laya Rafiee, Sharut Gupta, Stan Matwin, Mohammad Havaei:
Minimizing Client Drift in Federated Learning via Adaptive Bias Estimation. CoRR abs/2204.13170 (2022) - [i39]Nader Zare, Arad Firouzkouhi, Omid Amini, Mahtab Sarvmaili, Aref Sayareh, Saba Ramezani Rad, Stan Matwin, Amílcar Soares:
CYRUS Soccer Simulation 2D Team Description Paper 2022. CoRR abs/2205.10953 (2022) - [i38]Nader Zare, Aref Sayareh, Mahtab Sarvmaili, Omid Amini, Amílcar Soares, Stan Matwin:
CYRUS Soccer Simulation 2D Team Description Paper 2021. CoRR abs/2206.02310 (2022) - [i37]Martha Dais Ferreira, Gabriel Spadon, Amílcar Soares, Stan Matwin:
A semi-supervised geometric-driven methodology for supervised fishing activity detection on multi-source AIS tracking messages. CoRR abs/2207.05514 (2022) - [i36]Nader Zare, Omid Amini, Aref Sayareh, Mahtab Sarvmaili, Arad Firouzkouhi, Saba Ramezani Rad, Stan Matwin, Amílcar Soares:
Cyrus2D base: Source Code Base for RoboCup 2D Soccer Simulation League. CoRR abs/2211.08585 (2022) - [i35]Bettina Berendt, Stan Matwin, Chiara Renso, Fran Meissner, Francesca Pratesi, Alessandra Raffaetà, Geoffrey Rockwell:
Mobility Data Mining: from Technical to Ethical (Dagstuhl Seminar 22022). Dagstuhl Reports 12(1): 35-66 (2022) - 2021
- [j66]Jianzhe Zhao, Jie Mei, Stan Matwin, Yukai Su, Yuancheng Yang:
Risk-Aware Individual Trajectory Data Publishing With Differential Privacy. IEEE Access 9: 7421-7438 (2021) - [j65]Mirco Nanni, Gennady L. Andrienko, Albert-László Barabási, Chiara Boldrini, Francesco Bonchi, Ciro Cattuto, Francesca Chiaromonte, Giovanni Comandè, Marco Conti, Mark Coté, Frank Dignum, Virginia Dignum, Josep Domingo-Ferrer, Paolo Ferragina, Fosca Giannotti, Riccardo Guidotti, Dirk Helbing, Kimmo Kaski, János Kertész, Sune Lehmann, Bruno Lepri, Paul Lukowicz, Stan Matwin, David Megías Jiménez, Anna Monreale, Katharina Morik, Nuria Oliver, Andrea Passarella, Andrea Passerini, Dino Pedreschi, Alex Pentland, Fabio Pianesi, Francesca Pratesi, Salvatore Rinzivillo, Salvatore Ruggieri, Arno Siebes, Vicenç Torra, Roberto Trasarti, Jeroen van den Hoven, Alessandro Vespignani:
Give more data, awareness and control to individual citizens, and they will help COVID-19 containment. Ethics Inf. Technol. 23(S1): 1-6 (2021) - [j64]Iraklis Varlamis, Ioannis Kontopoulos, Konstantinos Tserpes, Mohammad Etemad, Amílcar Soares Júnior, Stan Matwin:
Building navigation networks from multi-vessel trajectory data. GeoInformatica 25(1): 69-97 (2021) - [j63]Mohammad Etemad, Amílcar Soares Júnior, Elham Etemad, Jordan Rose, Luís Torgo, Stan Matwin:
SWS: an unsupervised trajectory segmentation algorithm based on change detection with interpolation kernels. GeoInformatica 25(2): 269-289 (2021) - [j62]Chiara Renso, Vania Bogorny, Konstantinos Tserpes, Stan Matwin, José Antônio Fernandes de Macêdo:
Multiple-aspect analysis of semantic trajectories(MASTER). Int. J. Geogr. Inf. Sci. 35(4): 763-766 (2021) - [j61]Fernando Henrique Oliveira Abreu, Amílcar Soares Júnior, Fernando V. Paulovich, Stan Matwin:
A Trajectory Scoring Tool for Local Anomaly Detection in Maritime Traffic Using Visual Analytics. ISPRS Int. J. Geo Inf. 10(6): 412 (2021) - [j60]Fateha Khanam Bappee, Amílcar Soares, Lucas May Petry, Stan Matwin:
Examining the impact of cross-domain learning on crime prediction. J. Big Data 8(1): 96 (2021) - [j59]Bruno Brandoli, André R. de Geus, Jefferson R. Souza, Gabriel Spadon, Amílcar Soares Júnior, José F. Rodrigues Jr., Jerzy Komorowski, Stan Matwin:
Aircraft Fuselage Corrosion Detection Using Artificial Intelligence. Sensors 21(12): 4026 (2021) - [j58]Bruno Neiva Moreno, Valéria Cesário Times, Stan Matwin:
Representation and analysis of spatiotemporal encounters published in online social networks. Soc. Netw. Anal. Min. 11(1): 93 (2021) - [c211]Mahtab Sarvmaili, Amílcar Soares, Riccardo Guidotti, Anna Monreale, Fosca Giannotti, Dino Pedreschi, Stan Matwin:
A modularized framework for explaining hierarchical attention networks on text classifiers. Canadian AI 2021 - [c210]Fatemeh Rahimi, Evangelos E. Milios, Stan Matwin:
MTLV: a library for building deep multi-task learning architectures. DocEng 2021: 8:1-8:4 - [c209]Fernando Henrique Oliveira Abreu, Amílcar Soares, Fernando V. Paulovich, Stan Matwin:
Local Anomaly Detection In Maritime Traffic Using Visual Analytics. EDBT/ICDT Workshops 2021 - [c208]Giulia Rovinelli, Stan Matwin, Fabio Pranovi, Elisabetta Russo, Claudio Silvestri, Marta Simeoni, Alessandra Raffaetà:
Multiple aspect trajectories: a case study on fishing vessels in the Northern Adriatic sea. EDBT/ICDT Workshops 2021 - [c207]Lubna Eljabu, Mohammad Etemad, Stan Matwin:
Anomaly Detection in Maritime Domain based on Spatio-Temporal Analysis of AIS Data Using Graph Neural Networks. ICVISP 2021: 142-147 - [c206]Nader Zare, Mahtab Sarvmaili, Aref Sayareh, Omid Amini, Stan Matwin, Amílcar Soares:
Engineering Features to Improve Pass Prediction in Soccer Simulation 2D Games. RoboCup 2021: 140-152 - [c205]Nader Zare, Omid Amini, Aref Sayareh, Mahtab Sarvmaili, Arad Firouzkouhi, Stan Matwin, Amílcar Soares:
Improving Dribbling, Passing, and Marking Actions in Soccer Simulation 2D Games Using Machine Learning. RoboCup 2021: 340-351 - [c204]Sri Harsha Dumpala, Rudolf Uher, Stan Matwin, Michael Kiefte, Sageev Oore:
Sine-Wave Speech and Privacy-Preserving Depression Detection. SMM 2021 - [i34]Hamed Jelodar, Rita Orji, Stan Matwin, Swarna Weerasinghe, Oladapo Oyebode, Yongli Wang:
Artificial Intelligence for Emotion-Semantic Trending and People Emotion Detection During COVID-19 Social Isolation. CoRR abs/2101.06484 (2021) - [i33]Nader Zare, Bruno Brandoli, Mahtab Sarvmaili, Amílcar Soares, Stan Matwin:
Continuous Control with Deep Reinforcement Learning for Autonomous Vessels. CoRR abs/2106.14130 (2021) - [i32]Stan Matwin, Aristides Milios, Pawel Pralat, Amílcar Soares, François Théberge:
Survey of Generative Methods for Social Media Analysis. CoRR abs/2112.07041 (2021) - 2020
- [j57]Mirco Nanni, Gennady L. Andrienko, Albert-László Barabási, Chiara Boldrini, Francesco Bonchi, Ciro Cattuto, Francesca Chiaromonte, Giovanni Comandè, Marco Conti, Mark Coté, Frank Dignum, Virginia Dignum, Josep Domingo-Ferrer, Paolo Ferragina, Fosca Giannotti, Riccardo Guidotti, Dirk Helbing, Kimmo Kaski, János Kertész, Sune Lehmann, Bruno Lepri, Paul Lukowicz, Stan Matwin, David Megías, Anna Monreale, Katharina Morik, Nuria Oliver, Andrea Passarella, Andrea Passerini, Dino Pedreschi, Alex Pentland, Fabio Pianesi, Francesca Pratesi, Salvatore Rinzivillo, Salvatore Ruggieri, Arno Siebes, Vicenç Torra, Roberto Trasarti, Jeroen van den Hoven, Alessandro Vespignani:
Give more data, awareness and control to individual citizens, and they will help COVID-19 containment. Trans. Data Priv. 13(1): 61-66 (2020) - [c203]Riccardo Guidotti, Anna Monreale, Stan Matwin, Dino Pedreschi:
Explaining Image Classifiers Generating Exemplars and Counter-Exemplars from Latent Representations. AAAI 2020: 13665-13668 - [c202]Mohammad Etemad, Zahra Etemad, Amílcar Soares Júnior, Vania Bogorny, Stan Matwin, Luís Torgo:
Wise Sliding Window Segmentation: A Classification-Aided Approach for Trajectory Segmentation. Canadian AI 2020: 208-219 - [c201]Mohammad Etemad, Nader Zare, Mahtab Sarvmaili, Amílcar Soares Júnior, Bruno Brandoli Machado, Stan Matwin:
Using Deep Reinforcement Learning Methods for Autonomous Vessels in 2D Environments. Canadian AI 2020: 220-231 - [c200]Gashin Ghazizadeh, Mirerfan Gheibi, Stan Matwin:
CB-DBSCAN: A Novel Clustering Algorithm for Adjacent Clusters with Different Densities. Canadian AI 2020: 232-237 - [c199]Lucas May Petry, Amílcar Soares Júnior, Vania Bogorny, Bruno Brandoli, Stan Matwin:
Challenges in Vessel Behavior and Anomaly Detection: From Classical Machine Learning to Deep Learning. Canadian AI 2020: 401-407 - [c198]Emanuele Carlini, Vinicius Monteiro de Lira, Amílcar Soares Júnior, Mohammad Etemad, Bruno Brandoli Machado, Stan Matwin:
Uncovering vessel movement patterns from AIS data with graph evolution analysis. EDBT/ICDT Workshops 2020 - [c197]Xiang Jiang, Qicheng Lao, Stan Matwin, Mohammad Havaei:
Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation. ICML 2020: 4816-4827 - [c196]Habibeh Naderi, Behrouz Haji Soleimani, Stan Matwin:
Generating High-Fidelity Images with Disentangled Adversarial VAEs and Structure-Aware Loss. IJCNN 2020: 1-8 - [c195]Xiaoyu Yang, Stephen Obadinma, Huasha Zhao, Qiong Zhang, Stan Matwin, Xiaodan Zhu:
SemEval-2020 Task 5: Counterfactual Recognition. SemEval@COLING 2020: 322-335 - [e12]Annalisa Appice, Grigorios Tsoumakas, Yannis Manolopoulos, Stan Matwin:
Discovery Science - 23rd International Conference, DS 2020, Thessaloniki, Greece, October 19-21, 2020, Proceedings. Lecture Notes in Computer Science 12323, Springer 2020, ISBN 978-3-030-61526-0 [contents] - [e11]Konstantinos Tserpes, Chiara Renso, Stan Matwin:
Multiple-Aspect Analysis of Semantic Trajectories - First International Workshop, MASTER 2019, Held in Conjunction with ECML-PKDD 2019, Würzburg, Germany, September 16, 2019, Proceedings. Lecture Notes in Computer Science 11889, Springer 2020, ISBN 978-3-030-38080-9 [contents] - [d1]Xiaoyu Yang, Stephen Obadinma, Huasha Zhao, Qiong Zhang, Stan Matwin, Xiaodan Zhu:
SemEval-2020 Task 5: Modelling Causal Reasoning in Language: Detecting Counterfactuals. Zenodo, 2020
- [i31]Oliver S. Kirsebom, Fábio Frazão, Yvan Simard, Nathalie Roy, Stan Matwin, Samuel Giard:
Performance of a Deep Neural Network at Detecting North Atlantic Right Whale Upcalls. CoRR abs/2001.09127 (2020) - [i30]Riccardo Guidotti, Anna Monreale, Stan Matwin, Dino Pedreschi:
Black Box Explanation by Learning Image Exemplars in the Latent Feature Space. CoRR abs/2002.03746 (2020) - [i29]Mohammad Etemad, Zahra Etemad, Amílcar Soares Júnior, Vania Bogorny, Stan Matwin, Luís Torgo:
Wise Sliding Window Segmentation: A classification-aided approach for trajectory segmentation. CoRR abs/2003.10248 (2020) - [i28]Mohammad Etemad, Nader Zare, Mahtab Sarvmaili, Amílcar Soares Júnior, Bruno Brandoli Machado, Stan Matwin:
Using Deep Reinforcement Learning Methods for Autonomous Vessels in 2D Environments. CoRR abs/2003.10249 (2020) - [i27]Lucas May Petry, Amílcar Soares Júnior, Vania Bogorny, Bruno Brandoli, Stan Matwin:
Challenges in Vessel Behavior and Anomaly Detection: From Classical Machine Learning to Deep Learning. CoRR abs/2004.03722 (2020) - [i26]Xiang Jiang, Qicheng Lao, Stan Matwin, Mohammad Havaei:
Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation. CoRR abs/2006.04996 (2020) - [i25]Fateha Khanam Bappee, Lucas May Petry, Amílcar Soares Júnior, Stan Matwin:
Analyzing the Impact of Foursquare and Streetlight Data with Human Demographics on Future Crime Prediction. CoRR abs/2006.07516 (2020) - [i24]Farshid Varno, Lucas May Petry, Lisa Di-Jorio, Stan Matwin:
Learn Faster and Forget Slower via Fast and Stable Task Adaptation. CoRR abs/2007.01388 (2020) - [i23]Xiaoyu Yang, Stephen Obadinma, Huasha Zhao, Qiong Zhang, Stan Matwin, Xiaodan Zhu:
SemEval-2020 Task 5: Counterfactual Recognition. CoRR abs/2008.00563 (2020) - [i22]Oladapo Oyebode, Chinenye Ndulue, Dinesh Mulchandani, Banuchitra Suruliraj, Ashfaq Adib, Fidelia Anulika Orji, Evangelos E. Milios, Stan Matwin, Rita Orji:
COVID-19 Pandemic: Identifying Key Issues using Social Media and Natural Language Processing. CoRR abs/2008.10022 (2020) - [i21]Gabriel Spadon, Shenda Hong, Bruno Brandoli, Stan Matwin, José F. Rodrigues Jr., Jimeng Sun:
Pay Attention to Evolution: Time Series Forecasting with Deep Graph-Evolution Learning. CoRR abs/2008.12833 (2020)
2010 – 2019
- 2019
- [j56]Ahmad Pesaranghader, Stan Matwin, Marina Sokolova, Ali Pesaranghader:
deepBioWSD: effective deep neural word sense disambiguation of biomedical text data. J. Am. Medical Informatics Assoc. 26(5): 438-446 (2019) - [j55]Stan Matwin, Luca Tesei, Roberto Trasarti:
Computational modelling and data-driven techniques for systems analysis. J. Intell. Inf. Syst. 52(3): 473-475 (2019) - [c194]Behrouz Haji Soleimani, Stan Matwin:
Fast PMI-Based Word Embedding with Efficient Use of Unobserved Patterns. AAAI 2019: 7031-7038 - [c193]Sima Sharifirad, Stan Matwin:
Using Attention-based Bidirectional LSTM to Identify Different Categories of Offensive Language Directed Toward Female Celebrities. WNLP@ACL 2019: 46-48 - [c192]Mohammad Etemad, Amílcar Soares Júnior, Arazoo Hoseyni, Jordan Rose, Stan Matwin:
A Trajectory Segmentation Algorithm Based on Interpolation-based Change Detection Strategies. EDBT/ICDT Workshops 2019 - [c191]Mohammad Etemad, Amílcar Soares Júnior, Stan Matwin, Luís Torgo:
On Feature Selection and Evaluation of Transportation Mode Prediction Strategies. EDBT/ICDT Workshops 2019 - [c190]Amílcar Soares Júnior, Jordan Rose, Mohammad Etemad, Chiara Renso, Stan Matwin:
VISTA: A visual analytics platform for semantic annotation of trajectories. EDBT 2019: 570-573 - [c189]Iraklis Varlamis, Konstantinos Tserpes, Mohammad Etemad, Amílcar Soares Júnior, Stan Matwin:
A Network Abstraction of Multi-vessel Trajectory Data for Detecting Anomalies. EDBT/ICDT Workshops 2019 - [c188]Aristides Milios, Konstantina Bereta, Konstantinos Chatzikokolakis, Dimitris Zissis, Stan Matwin:
Automatic Fusion of Satellite Imagery and AIS data for Vessel Detection. FUSION 2019: 1-5 - [c187]Duong Nguyen, Oliver S. Kirsebom, Fábio Frazão, Ronan Fablet, Stan Matwin:
Recurrent Neural Networks with Stochastic Layers for Acoustic Novelty Detection. ICASSP 2019: 765-769 - [c186]Xiang Jiang, Mohammad Havaei, Farshid Varno, Gabriel Chartrand, Nicolas Chapados, Stan Matwin:
Learning to Learn with Conditional Class Dependencies. ICLR (Poster) 2019 - [c185]Amílcar Soares, Renata Dividino, Fernando Henrique Oliveira Abreu, Matthew Brousseau, Anthony W. Isenor, Sean Webb, Stan Matwin:
CRISIS: Integrating AIS and Ocean Data Streams Using Semantic Web Standards for Event Detection. ICMCIS 2019: 1-7 - [c184]Xiang Jiang, Liqiang Ding, Mohammad Havaei, Andrew Jesson, Stan Matwin:
Task Adaptive Metric Space for Medium-Shot Medical Image Classification. MICCAI (1) 2019: 147-155 - [c183]Pedram Adibi, Fabio Pranovi, Alessandra Raffaetà, Elisabetta Russo, Claudio Silvestri, Marta Simeoni, Amílcar Soares Júnior, Stan Matwin:
Predicting Fishing Effort and Catch Using Semantic Trajectories and Machine Learning. MASTER@PKDD/ECML 2019: 83-99 - [c182]Riccardo Guidotti, Anna Monreale, Stan Matwin, Dino Pedreschi:
Black Box Explanation by Learning Image Exemplars in the Latent Feature Space. ECML/PKDD (1) 2019: 189-205 - [c181]Mark Thomas, Bruce Martin, Katie Kowarski, Briand J. Gaudet, Stan Matwin:
Marine Mammal Species Classification Using Convolutional Neural Networks and a Novel Acoustic Representation. ECML/PKDD (3) 2019: 290-305 - [i20]Witold Dzwinel, Rafal Wcislo, Stan Matwin:
2-D Embedding of Large and High-dimensional Data with Minimal Memory and Computational Time Requirements. CoRR abs/1902.01108 (2019) - [i19]Sima Sharifirad, Borna Jafarpour, Stan Matwin:
How is Your Mood When Writing Sexist tweets? Detecting the Emotion Type and Intensity of Emotion Using Natural Language Processing Techniques. CoRR abs/1902.03089 (2019) - [i18]Duong Nguyen, Oliver S. Kirsebom, Fábio Frazão, Ronan Fablet, Stan Matwin:
Recurrent Neural Networks with Stochastic Layers for Acoustic Novelty Detection. CoRR abs/1902.04980 (2019) - [i17]Sima Sharifirad, Stan Matwin:
When a Tweet is Actually Sexist. A more Comprehensive Classification of Different Online Harassment Categories and The Challenges in NLP. CoRR abs/1902.10584 (2019) - [i16]Farshid Varno, Behrouz Haji Soleimani, Marzie Saghayi, Lisa Di-Jorio, Stan Matwin:
Efficient Neural Task Adaptation by Maximum Entropy Initialization. CoRR abs/1905.10698 (2019) - [i15]Mark Thomas, Bruce Martin, Katie Kowarski, Briand J. Gaudet, Stan Matwin:
Marine Mammal Species Classification using Convolutional Neural Networks and a Novel Acoustic Representation. CoRR abs/1907.13188 (2019) - [i14]Lucas May Petry, Amílcar Soares Júnior, Vania Bogorny, Stan Matwin:
Unsupervised Behavior Change Detection in Multidimensional Data Streams for Maritime Traffic Monitoring. CoRR abs/1908.05103 (2019) - [i13]Habibeh Naderi, Behrouz Haji Soleimani, Sheri Rempel, Stan Matwin, Rudolf Uher:
Multimodal Deep Learning for Mental Disorders Prediction from Audio Speech Samples. CoRR abs/1909.01067 (2019) - 2018
- [j54]Elnaz Bigdeli, Mahdi Mohammadi, Bijan Raahemi, Stan Matwin:
Incremental anomaly detection using two-layer cluster-based structure. Inf. Sci. 429: 315-331 (2018) - [j53]Claudivan Cruz Lopes, Valéria Cesário Times, Stan Matwin, Cristina Dutra de Aguiar Ciferri, Ricardo Rodrigues Ciferri:
An Encryption Methodology for Enabling the Use of Data Warehouses on the Cloud. Int. J. Data Warehous. Min. 14(4): 38-66 (2018) - [c180]Behrouz Haji Soleimani, Stan Matwin:
Spectral Word Embedding with Negative Sampling. AAAI 2018: 5481-5487 - [c179]Sima Sharifirad, Borna Jafarpour, Stan Matwin:
Boosting Text Classification Performance on Sexist Tweets by Text Augmentation and Text Generation Using a Combination of Knowledge Graphs. ALW 2018: 107-114 - [c178]Ahmad Pesaranghader, Ali Pesaranghader, Stan Matwin, Marina Sokolova:
One Single Deep Bidirectional LSTM Network for Word Sense Disambiguation of Text Data. Canadian AI 2018: 96-107 - [c177]Behrouz Haji Soleimani, Stan Matwin:
Dimensionality Reduction and Visualization by Doubly Kernelized Unit Ball Embedding. Canadian AI 2018: 224-230 - [c176]Mohammad Etemad, Amílcar Soares Júnior, Stan Matwin:
Predicting Transportation Modes of GPS Trajectories Using Feature Engineering and Noise Removal. Canadian AI 2018: 259-264 - [c175]Fateha Khanam Bappee, Amílcar Soares Júnior, Stan Matwin:
Predicting Crime Using Spatial Features. Canadian AI 2018: 367-373 - [c174]Xuan Liu, Xiaoguang Wang, Stan Matwin:
Improving the Interpretability of Deep Neural Networks with Knowledge Distillation. ICDM Workshops 2018: 905-912 - [c173]Xuan Liu, Xiaoguang Wang, Stan Matwin:
Interpretable Deep Convolutional Neural Networks via Meta-learning. IJCNN 2018: 1-9 - [c172]Amílcar Soares Júnior, Valéria Cesário Times, Chiara Renso, Stan Matwin, Lucídio A. F. Cabral:
A Semi-Supervised Approach for the Semantic Segmentation of Trajectories. MDM 2018: 145-154 - [c171]Luís Torgo, Stan Matwin, Nathalie Japkowicz, Bartosz Krawczyk, Nuno Moniz, Paula Branco:
2nd Workshop on Learning with Imbalanced Domains: Preface. LIDTA@ECML/PKDD 2018: 1-7 - [c170]Luís Torgo, Stan Matwin, Gary Weiss, Nuno Moniz, Paula Branco:
Cost-Sensitive Learning: Preface. COST@SDM 2018: 1-3 - [c169]Habibeh Naderi, Behrouz Haji Soleimani, Saif M. Mohammad, Svetlana Kiritchenko, Stan Matwin:
DeepMiner at SemEval-2018 Task 1: Emotion Intensity Recognition Using Deep Representation Learning. SemEval@NAACL-HLT 2018: 305-312 - [i12]Xuan Liu, Xiaoguang Wang, Stan Matwin:
Interpretable Deep Convolutional Neural Networks via Meta-learning. CoRR abs/1802.00560 (2018) - [i11]Ahmad Pesaranghader, Ali Pesaranghader, Stan Matwin, Marina Sokolova:
One Single Deep Bidirectional LSTM Network for Word Sense Disambiguation of Text Data. CoRR abs/1802.09059 (2018) - [i10]Mohammad Etemad, Amílcar Soares Júnior, Stan Matwin:
Predicting Transportation Modes of GPS Trajectories using Feature Engineering and Noise Removal. CoRR abs/1802.10164 (2018) - [i9]Fateha Khanam Bappee, Amílcar Soares Júnior, Stan Matwin:
Predicting Crime Using Spatial Features. CoRR abs/1803.04474 (2018) - [i8]Xiang Jiang, Mohammad Havaei, Gabriel Chartrand, Hassan Chouaib, Thomas Vincent, Andrew Jesson, Nicolas Chapados, Stan Matwin:
On the Importance of Attention in Meta-Learning for Few-Shot Text Classification. CoRR abs/1806.00852 (2018) - [i7]Mohammad Etemad, Amílcar Soares Júnior, Stan Matwin:
On feature selection and evaluation of transportation mode prediction strategies. CoRR abs/1808.03096 (2018) - [i6]Xuan Liu, Xiaoguang Wang, Stan Matwin:
Improving the Interpretability of Deep Neural Networks with Knowledge Distillation. CoRR abs/1812.10924 (2018) - 2017
- [j52]Amílcar Soares Júnior, Chiara Renso, Stan Matwin:
ANALYTiC: An Active Learning System for Trajectory Classification. IEEE Computer Graphics and Applications 37(5): 28-39 (2017) - [j51]Nathalie Japkowicz, Stan Matwin:
Special issue on discovery science. Mach. Learn. 106(6): 741-743 (2017) - [j50]Elnaz Bigdeli, Mahdi Mohammadi, Bijan Raahemi, Stan Matwin:
A fast and noise resilient cluster-based anomaly detection. Pattern Anal. Appl. 20(1): 183-199 (2017) - [j49]Yasser Jafer, Stan Matwin, Marina Sokolova:
A Multi-dimensional Privacy-aware Evaluation Function in Automatic Feature Selection. Trans. Data Priv. 10(3): 145-174 (2017) - [c168]Aaron Gerow, Mingyang Zhou, Stan Matwin, Feng Shi:
Reflexive Regular Equivalence for Bipartite Data. Canadian AI 2017: 71-77 - [c167]Sima Sharifirad, Stan Matwin:
Deep Multi-cultural Graph Representation Learning. Canadian AI 2017: 407-410 - [c166]Xiang Jiang, Erico N. de Souza, Ahmad Pesaranghader, Baifan Hu, Daniel L. Silver, Stan Matwin:
TrajectoryNet: an embedded GPS trajectory representation for point-based classification using recurrent neural networks. CASCON 2017: 192-200 - [c165]Habibeh Naderi, Behrouz Haji Soleimani, Stan Matwin:
Manifold Learning of Overcomplete Feature Spaces in a Multimodal Biometric Recognition System of Iris and Palmprint. CRV 2017: 191-196 - [c164]Xiang Jiang, Erico N. de Souza, Xuan Liu, Behrouz Haji Soleimani, Xiaoguang Wang, Daniel L. Silver, Stan Matwin:
Partition-wise Recurrent Neural Networks for Point-based AIS Trajectory Classification. ESANN 2017 - [c163]Xiang Jiang, Xuan Liu, Erico N. de Souza, Baifan Hu, Daniel L. Silver, Stan Matwin:
Improving point-based AIS trajectory classification with partition-wise gated recurrent units. IJCNN 2017: 4044-4051 - [c162]Lulu Huang, Stan Matwin, Eder J. de Carvalho, Rosane Minghim:
Active Learning with Visualization for Text Data. ESIDA@IUI 2017: 69-74 - [r2]Stan Matwin:
Privacy-Related Aspects and Techniques. Encyclopedia of Machine Learning and Data Mining 2017: 1006-1013 - [i5]Aaron Gerow, Mingyang Zhou, Stan Matwin, Feng Shi:
Reflexive Regular Equivalence for Bipartite Data. CoRR abs/1702.04956 (2017) - [i4]Marina Sokolova, Vera Sazonova, Kanyi Huang, Rudraneel Chakraboty, Stan Matwin:
Studying Positive Speech on Twitter. CoRR abs/1702.08866 (2017) - [i3]Xiang Jiang, Erico N. de Souza, Ahmad Pesaranghader, Baifan Hu, Daniel L. Silver, Stan Matwin:
TrajectoryNet: An Embedded GPS Trajectory Representation for Point-based Classification Using Recurrent Neural Networks. CoRR abs/1705.02636 (2017) - 2016
- [j48]Ahmad Pesaranghader, Stan Matwin, Marina Sokolova, Robert G. Beiko:
simDEF: definition-based semantic similarity measure of gene ontology terms for functional similarity analysis of genes. Bioinform. 32(9): 1380-1387 (2016) - [j47]Luís Paulo F. Garcia, Ana Carolina Lorena, Stan Matwin, André Carlos Ponce de Leon Ferreira de Carvalho:
Ensembles of label noise filters: a ranking approach. Data Min. Knowl. Discov. 30(5): 1192-1216 (2016) - [c161]Xiang Jiang, Daniel L. Silver, Baifan Hu, Erico N. de Souza, Stan Matwin:
Fishing Activity Detection from AIS Data Using Autoencoders. Canadian AI 2016: 33-39 - [c160]Tomasz Tajmajer, Malwina Splawinska, Piotr Wasilewski, Stan Matwin:
Predicting annual average daily highway traffic from large data and very few measurements. IEEE BigData 2016: 1493-1501 - [c159]Habibeh Naderi, Behrouz Haji Soleimani, Stan Matwin, Babak Nadjar Araabi, Hamid Soltanian-Zadeh:
Fusing Iris, Palmprint and Fingerprint in a Multi-biometric Recognition System. CRV 2016: 327-334 - [c158]Stan Matwin:
Big Water Meets Big Data: Analytics of the AIS Ship Tracking Data. FedCSIS 2016: 1 - [c157]Baifan Hu, Xiang Jiang, Erico N. de Souza, Ronald Pelot, Stan Matwin:
Identifying Fishing Activities from AIS Data with Conditional Random Fields. FedCSIS 2016: 47-52 - [c156]Hossein Sarshar, Stan Matwin:
Using Classification in the Preprocessing Step on Wi-Fi Data as an Enabler of Physical Analytics. ICMLA 2016: 944-949 - [c155]Behrouz Haji Soleimani, Stan Matwin:
Nonlinear Dimensionality Reduction by Unit Ball Embedding (UBE) and Its Application to Image Clustering. ICMLA 2016: 983-988 - [c154]Denis Moreira dos Reis, Peter A. Flach, Stan Matwin, Gustavo E. A. P. A. Batista:
Fast Unsupervised Online Drift Detection Using Incremental Kolmogorov-Smirnov Test. KDD 2016: 1545-1554 - [p7]Marina Sokolova, Stan Matwin:
Personal Privacy Protection in Time of Big Data. Challenges in Computational Statistics and Data Mining 2016: 365-380 - [e10]Peggy Cellier, Thierry Charnois, Andreas Hotho, Stan Matwin, Marie-Francine Moens, Yannick Toussaint:
Proceedings of the Workshop on Interactions between Data Mining and Natural Language Processing, DMNLP 2016, co-located with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2016, Riva del Garda, Italy, September 23, 2016. CEUR Workshop Proceedings 1646, CEUR-WS.org 2016 [contents] - [e9]Stan Matwin, Jan Mielniczuk:
Challenges in Computational Statistics and Data Mining. Studies in Computational Intelligence 605, Springer 2016, ISBN 978-3-319-18780-8 [contents] - [i2]Kambiz Ghazinour, Stan Matwin, Marina Sokolova:
YOURPRIVACYPROTECTOR, A recommender system for privacy settings in social networks. CoRR abs/1602.01937 (2016) - [i1]Marina Sokolova, Kanyi Huang, Stan Matwin, Joshua Ramisch, Vera Sazonova, Renee Black, Chris Orwa, Sidney Ochieng, Nanjira Sambuli:
Topic Modelling and Event Identification from Twitter Textual Data. CoRR abs/1608.02519 (2016) - 2015
- [j46]Ahmed Ali Abdalla Esmin, Rodrigo A. Coelho, Stan Matwin:
A review on particle swarm optimization algorithm and its variants to clustering high-dimensional data. Artif. Intell. Rev. 44(1): 23-45 (2015) - [j45]Amílcar Soares Júnior, Bruno Neiva Moreno, Valéria Cesário Times, Stan Matwin, Lucídio dos Anjos Formiga Cabral:
GRASP-UTS: an algorithm for unsupervised trajectory segmentation. Int. J. Geogr. Inf. Sci. 29(1): 46-68 (2015) - [j44]Xuan Liu, Xiaoguang Wang, Stan Matwin, Nathalie Japkowicz:
Meta-MapReduce for scalable data mining. J. Big Data 2: 14 (2015) - [c153]Yasser Jafer, Stan Matwin, Marina Sokolova:
Privacy-aware Wrappers. Canadian AI 2015: 130-138 - [c152]Behrouz Haji Soleimani, Stan Matwin, Erico N. de Souza:
A Density-Penalized Distance Measure for Clustering. Canadian AI 2015: 238-249 - [c151]Elnaz Bigdeli, Mahdi Mohammadi, Bijan Raahemi, Stan Matwin:
Incremental Cluster Updating Using Gaussian Mixture Model. Canadian AI 2015: 264-272 - [c150]Joanna Ng, Frank Dehne, Stan Matwin, Herna L. Viktor, Olga Baysal:
Data science workshop: experience driven analytics. CASCON 2015: 344-346 - [c149]Mohammad Alaggan, Sébastien Gambs, Stan Matwin, Mohammed Tuhin:
Sanitization of Call Detail Records via Differentially-Private Bloom Filters. DBSec 2015: 223-230 - [c148]Behrouz Haji Soleimani, Erico N. de Souza, Casey Hilliard, Stan Matwin:
Anomaly detection in maritime data based on geometrical analysis of trajectories. FUSION 2015: 1100-1105 - [c147]Bo Liu, Erico N. de Souza, Casey Hilliard, Stan Matwin:
Ship movement anomaly detection using specialized distance measures. FUSION 2015: 1113-1120 - [c146]Marcin Sydow, Cristina Ioana Muntean, Franco Maria Nardini, Stan Matwin, Fabrizio Silvestri:
MUSETS: Diversity-Aware Web Query Suggestions for Shortening User Sessions. ISMIS 2015: 237-247 - [c145]Parinaz Sobhani, Diana Inkpen, Stan Matwin:
From Argumentation Mining to Stance Classification. ArgMining@HLT-NAACL 2015: 67-77 - [c144]Bruno Neiva Moreno, Valéria Cesário Times, Stan Matwin:
A spatio-temporal network model to represent and analyze LBSNs. PerCom Workshops 2015: 142-147 - [c143]Yasser Jafer, Stan Matwin, Marina Sokolova:
A framework for a privacy-aware feature selection evaluation measure. PST 2015: 62-69 - [p6]Stan Matwin, Jordi Nin, Morvarid Sehatkar, Tomasz Szapiro:
A Review of Attribute Disclosure Control. Advanced Research in Data Privacy 2015: 41-61 - [e8]Nathalie Japkowicz, Stan Matwin:
Discovery Science - 18th International Conference, DS 2015, Banff, AB, Canada, October 4-6, 2015, Proceedings. Lecture Notes in Computer Science 9356, Springer 2015, ISBN 978-3-319-24281-1 [contents] - [e7]Peggy Cellier, Thierry Charnois, Andreas Hotho, Stan Matwin, Marie-Francine Moens, Yannick Toussaint:
Proceedings of the Workshop on Interactions between Data Mining and Natural Language Processing, DMNLP 2015, co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2015), Porto, Portugal, September 07, 2015. CEUR Workshop Proceedings 1410, CEUR-WS.org 2015 [contents] - 2014
- [j43]Xiaoguang Wang, Xuan Liu, Nathalie Japkowicz, Stan Matwin:
Automated Approach To Classification Of Mine-Like Objects Using Multiple-Aspect Sonar Images. J. Artif. Intell. Soft Comput. Res. 4(2): 133-148 (2014) - [j42]Claudivan Cruz Lopes, Valéria Cesário Times, Stan Matwin:
Towards Cloud Data Warehouses of Multivalued Encrypted Values. J. Inf. Data Manag. 5(3): 335-348 (2014) - [j41]Amir Hossein Razavi, Stan Matwin, Joseph De Koninck, Ray Reza Amini:
Dream sentiment analysis using second order soft co-occurrences (SOSCO) and time course representations. J. Intell. Inf. Syst. 42(3): 393-413 (2014) - [j40]Vera Sazonova, Stan Matwin:
Combining Binary Classifiers for a Multiclass Problem with Differential Privacy. Trans. Data Priv. 7(1): 51-70 (2014) - [c142]Bernard Stepien, Amy P. Felty, Stan Matwin:
Challenges of Composing XACML Policies. ARES 2014: 234-241 - [c141]Yasser Jafer, Stan Matwin, Marina Sokolova:
Task Oriented Privacy Preserving Data Publishing Using Feature Selection. Canadian AI 2014: 143-154 - [c140]Xiaoguang Wang, Xuan Liu, Nathalie Japkowicz, Stan Matwin:
Ensemble of Multiple Kernel SVM Classifiers. Canadian AI 2014: 239-250 - [c139]Bruno Moreno, Amílcar Soares Júnior, Valéria Cesário Times, Patrícia C. A. R. Tedesco, Stan Matwin:
Weka-SAT: A Hierarchical Context-Based Inference Engine to Enrich Trajectories with Semantics. Canadian AI 2014: 333-338 - [c138]Yasser Jafer, Stan Matwin, Marina Sokolova:
Privacy-aware filter-based feature selection. IEEE BigData 2014: 1-5 - [c137]Xiaoguang Wang, Xuan Liu, Bo Liu, Erico N. de Souza, Stan Matwin:
Vessel route anomaly detection with Hadoop MapReduce. IEEE BigData 2014: 25-30 - [c136]Xiaoguang Wang, Xuan Liu, Stan Matwin:
A distributed instance-weighted SVM algorithm on large-scale imbalanced datasets. IEEE BigData 2014: 45-51 - [c135]Xiaoguang Wang, Xuan Liu, Stan Matwin, Nathalie Japkowicz, Hongyu Guo:
A multi-view two-level classification method for generalized multi-instance problems. IEEE BigData 2014: 104-111 - [c134]Xiaoguang Wang, Xuan Liu, Stan Matwin, Nathalie Japkowicz:
Applying instance-weighted support vector machines to class imbalanced datasets. IEEE BigData 2014: 112-118 - [c133]Bo Liu, Erico N. de Souza, Stan Matwin, Marcin Sydow:
Knowledge-based clustering of ship trajectories using density-based approach. IEEE BigData 2014: 603-608 - [c132]Xiaoguang Wang, Xuan Liu, Nathalie Japkowicz, Stan Matwin, Bao Nguyen:
Automatic Target Recognition using multiple-aspect sonar images. IEEE Congress on Evolutionary Computation 2014: 2330-2337 - [c131]Bernard Stepien, Amy P. Felty, Stan Matwin:
A non-technical XACML target editor for dynamic access control systems. CTS 2014: 150-157 - [c130]Claudivan Cruz Lopes, Valéria Cesário Times, Stan Matwin, Ricardo Rodrigues Ciferri, Cristina Dutra de Aguiar Ciferri:
Processing OLAP Queries over an Encrypted Data Warehouse Stored in the Cloud. DaWaK 2014: 195-207 - [c129]Morvarid Sehatkar, Stan Matwin:
Clustering-based Multidimensional Sequence Data Anonymization. EDBT/ICDT Workshops 2014: 385-389 - [c128]Fida Kamal Dankar, Renaud Brien, Carlisle Adams, Stan Matwin:
Secure Multi-Party linear Regression. EDBT/ICDT Workshops 2014: 406-414 - [c127]Fida Kamal Dankar, Khaled El Emam, Stan Matwin:
Efficient Private Information Retrieval for Geographical Aggregation. EUSPN/ICTH 2014: 497-502 - [c126]Yasser Jafer, Stan Matwin, Marina Sokolova:
Using Feature Selection to Improve the Utility of Differentially Private Data Publishing. EUSPN/ICTH 2014: 511-516 - [c125]Erico N. de Souza, Stan Matwin, Stenio F. L. Fernandes:
Traffic classification with on-line ensemble method. GIIS 2014: 1-4 - [c124]Elnaz Bigdeli, Mahdi Mohammadi, Bijan Raahemi, Stan Matwin:
Arbitrary Shape Cluster Summarization with Gaussian Mixture Model. KDIR 2014: 43-52 - [c123]Elnaz Bigdeli, Mahdi Mohammadi, Bijan Raahemi, Stan Matwin:
Cluster Summarization with Dense Region Detection. IC3K (Selected Papers) 2014: 68-83 - [c122]Parinaz Sobhani, Herna L. Viktor, Stan Matwin:
Learning from Imbalanced Data Using Ensemble Methods and Cluster-Based Undersampling. NFMCP 2014: 69-83 - [e6]Peggy Cellier, Thierry Charnois, Andreas Hotho, Stan Matwin, Marie-Francine Moens, Yannick Toussaint:
Proceedings of the 1st International Workshop on Interactions between Data Mining and Natural Language Processing co-located with The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, DMNLP@PKDD/ECML 2014, Nancy, France, September 15, 2014. CEUR Workshop Proceedings 1202, CEUR-WS.org 2014 [contents] - 2013
- [c121]Kambiz Ghazinour, Marina Sokolova, Stan Matwin:
Detecting Health-Related Privacy Leaks in Social Networks Using Text Mining Tools. Canadian AI 2013: 25-39 - [c120]Xiaoguang Wang, Stan Matwin, Nathalie Japkowicz, Xuan Liu:
Cost-Sensitive Boosting Algorithms for Imbalanced Multi-instance Datasets. Canadian AI 2013: 174-186 - [c119]Erico N. de Souza, Stan Matwin:
Improvements to Boosting with Data Streams. Canadian AI 2013: 248-255 - [c118]Xuan Liu, Xiaoguang Wang, Nathalie Japkowicz, Stan Matwin:
An Ensemble Method Based on AdaBoost and Meta-Learning. Canadian AI 2013: 278-285 - [c117]Xuan Liu, Xiaoguang Wang, Stan Matwin, Nathalie Japkowicz:
Meta-learning for large scale machine learning with MapReduce. IEEE BigData 2013: 105-110 - [c116]Kambiz Ghazinour, Stan Matwin, Marina Sokolova:
Monitoring and recommending privacy settings in social networks. EDBT/ICDT Workshops 2013: 164-168 - [c115]Erico N. de Souza, Stan Matwin, Stenio Fernandes:
Network traffic classification using AdaBoost Dynamic. ICC Workshops 2013: 1319-1324 - [c114]Xiaoguang Wang, Xuan Liu, Nathalie Japkowicz, Stan Matwin:
Resampling and Cost-Sensitive Methods for Imbalanced Multi-instance Learning. ICDM Workshops 2013: 808-816 - [c113]Houman Abbasian, Chris Drummond, Nathalie Japkowicz, Stan Matwin:
Inner Ensembles: Using Ensemble Methods Inside the Learning Algorithm. ECML/PKDD (3) 2013: 33-48 - [c112]Morvarid Sehatkar, Stan Matwin:
HALT: Hybrid anonymization of longitudinal transactions. PST 2013: 127-134 - [c111]Victoria Bobicev, Marina Sokolova, Khaled El Emam, Stan Matwin:
Authorship Attribution in Health Forums. RANLP 2013: 74-82 - [c110]Marina Sokolova, Stan Matwin, Yasser Jafer, David Schramm:
How Joe and Jane Tweet about Their Health: Mining for Personal Health Information on Twitter. RANLP 2013: 626-632 - [p5]Stan Matwin:
Privacy-Preserving Data Mining Techniques: Survey and Challenges. Discrimination and Privacy in the Information Society 2013: 209-221 - 2012
- [j39]Jin Huang, Jelber Sayyad-Shirabad, Stan Matwin, Jiang Su:
Improving multi-view semi-supervised learning with agreement-based sampling. Intell. Data Anal. 16(5): 745-761 (2012) - [j38]Stan Matwin, Vera Sazonova:
Direct comparison between support vector machine and multinomial naive Bayes algorithms for medical abstract classification. J. Am. Medical Informatics Assoc. 19(5): 917 (2012) - [c109]Bernard Stepien, Stan Matwin, Amy P. Felty:
An Algorithm for Compression of XACML Access Control Policy Sets by Recursive Subsumption. ARES 2012: 161-167 - [c108]Erico N. de Souza, Stan Matwin:
Improvements to AdaBoost Dynamic. Canadian AI 2012: 293-298 - [c107]Flavien Bouillot, Pascal Poncelet, Mathieu Roche, Dino Ienco, Elnaz Bigdeli, Stan Matwin:
French presidential elections: what are the most efficient measures for tweets? PLEAD@CIKM 2012: 23-30 - [c106]Xiaoguang Wang, Hang Shao, Nathalie Japkowicz, Stan Matwin, Xuan Liu, Alex Bourque, Bao Nguyen:
Using SVM with Adaptively Asymmetric MisClassification Costs for Mine-Like Objects Detection. ICMLA (2) 2012: 78-82 - [c105]Ahmed Ali Abdalla Esmin, Roberto L. de Oliveira Jr., Stan Matwin:
Hierarchical Classification Approach to Emotion Recognition in Twitter. ICMLA (2) 2012: 381-385 - [c104]Ahmed Ali Abdalla Esmin, Stan Matwin:
Data Clustering Using Hybrid Particle Swarm Optimization. IDEAL 2012: 159-166 - [c103]Flavien Bouillot, Phan Nhat Hai, Nicolas Béchet, Sandra Bringay, Dino Ienco, Stan Matwin, Pascal Poncelet, Mathieu Roche, Maguelonne Teisseire:
How to Extract Relevant Knowledge from Tweets? ISIP 2012: 111-120 - 2011
- [j37]Oana Frunza, Diana Inkpen, Stan Matwin, William Klement, Peter O'Blenis:
Exploiting the systematic review protocol for classification of medical abstracts. Artif. Intell. Medicine 51(1): 17-25 (2011) - [j36]Mikhail Jiline, Stan Matwin, Marcel Turcotte:
Annotation concept synthesis and enrichment analysis: a logic-based approach to the interpretation of high-throughput experiments. Bioinform. 27(17): 2391-2398 (2011) - [j35]Stan Matwin, Alexandre Kouznetsov, Diana Inkpen, Oana Frunza, Peter O'Blenis:
Letter: Performance of SVM and Bayesian classifiers on the systematic review classification task. J. Am. Medical Informatics Assoc. 18(1): 104-105 (2011) - [c102]William Klement, Szymon Wilk, Wojtek Michalowski, Stan Matwin:
Classifying Severely Imbalanced Data. Canadian AI 2011: 258-264 - [c101]Erico N. de Souza, Stan Matwin:
Extending AdaBoost to Iteratively Vary Its Base Classifiers. Canadian AI 2011: 384-389 - [c100]Svetlana Kiritchenko, Stan Matwin:
Email classification with co-training. CASCON 2011: 301-312 - [c99]Jiang Su, Jelber Sayyad Shirab, Stan Matwin:
Large Scale Text Classification using Semisupervised Multinomial Naive Bayes. ICML 2011: 97-104 - [c98]William Klement, Peter A. Flach, Nathalie Japkowicz, Stan Matwin:
Smooth Receiver Operating Characteristics (smROC) Curves. ECML/PKDD (2) 2011: 193-208 - [c97]Bernard Stepien, Stan Matwin, Amy P. Felty:
Advantages of a non-technical XACML notation in role-based models. PST 2011: 193-200 - 2010
- [j34]Javier Herranz, Stan Matwin, Jordi Nin, Vicenç Torra:
Classifying data from protected statistical datasets. Comput. Secur. 29(8): 875-890 (2010) - [j33]Stan Matwin, Alexandre Kouznetsov, Diana Inkpen, Oana Frunza, Peter O'Blenis:
A new algorithm for reducing the workload of experts in performing systematic reviews. J. Am. Medical Informatics Assoc. 17(4): 446-453 (2010) - [j32]Ken Farion, Wojtek Michalowski, Szymon Wilk, Dympna O'Sullivan, Stan Matwin:
A Tree-Based Decision Model to Support Prediction of the Severity of Asthma Exacerbations in Children. J. Medical Syst. 34(4): 551-562 (2010) - [c96]Bernard Stepien, Stan Matwin, Amy P. Felty:
Strategies for Reducing Risks of Inconsistencies in Access Control Policies. ARES 2010: 140-147 - [c95]Amir Hossein Razavi, Diana Inkpen, Sasha Uritsky, Stan Matwin:
Offensive Language Detection Using Multi-level Classification. Canadian AI 2010: 16-27 - [c94]Houman Abbasian, Chris Drummond, Nathalie Japkowicz, Stan Matwin:
Robustness of Classifiers to Changing Environments. Canadian AI 2010: 232-243 - [c93]Mikhail Jiline, Stan Matwin, Marcel Turcotte:
Annotation Concept Synthesis and Enrichment Analysis. Canadian AI 2010: 304-308 - [c92]Farid Seifi, Chris Drummond, Nathalie Japkowicz, Stan Matwin:
Improving Bayesian Learning Using Public Knowledge. Canadian AI 2010: 348-351 - [c91]Oana Frunza, Diana Inkpen, Stan Matwin:
Building Systematic Reviews Using Automatic Text Classification Techniques. COLING (Posters) 2010: 303-311 - [c90]Stan Matwin, Joseph De Koninck, Amir Hossein Razavi, Ray Reza Amini:
Classification of Dreams Using Machine Learning. ECAI 2010: 169-174 - [c89]Jin Huang, Jelber Sayyad-Shirabad, Stan Matwin, Jiang Su:
Improving Co-training with Agreement-Based Sampling. RSCTC 2010: 197-206 - [p4]Stan Matwin, Tomasz Szapiro:
Data Privacy: From Technology to Economics. Advances in Machine Learning II 2010: 43-74 - [r1]Stan Matwin:
Privacy-Related Aspects and Techniques. Encyclopedia of Machine Learning 2010: 795-801
2000 – 2009
- 2009
- [c88]William Klement, Peter A. Flach, Nathalie Japkowicz, Stan Matwin:
Cost-Based Sampling of Individual Instances. Canadian AI 2009: 86-97 - [c87]Alexandre Kouznetsov, Stan Matwin, Diana Inkpen, Amir Hossein Razavi, Oana Frunza, Morvarid Sehatkar, Leanne Seaward, Peter O'Blenis:
Classifying Biomedical Abstracts Using Committees of Classifiers and Collective Ranking Techniques. Canadian AI 2009: 224-228 - [c86]Jiang Su, Jelber Sayyad-Shirabad, Stan Matwin, Jin Huang:
Active Learning with Automatic Soft Labeling for Induction of Decision Trees. Canadian AI 2009: 241-244 - [c85]Javier Herranz, Stan Matwin, Pedro Meseguer, Jordi Nin:
A Cryptographic Solution for Private Distributed Simple Meeting Scheduling. CCIA 2009: 275-283 - [c84]Stan Matwin:
Privacy and Data Mining: New Developments and Challenges. EGC 2009: 1 - [c83]Amir Hossein Razavi, Stan Matwin, Diana Inkpen, Alexandre Kouznetsov:
Parameterized Contrast in Second Order Soft Co-occurrences: A Novel Text Representation Technique in Text Mining and Knowledge Extraction. ICDM Workshops 2009: 471-476 - [c82]Stan Matwin:
Image Analysis and Machine Learning: How to Foster a Stronger Connection? ICIAP 2009: 5 - [c81]Bernard Stepien, Amy P. Felty, Stan Matwin:
A Non-technical User-Oriented Display Notation for XACML Conditions. MCETECH 2009: 53-64 - 2008
- [c80]Szymon Wilk, Wojtek Michalowski, Dympna O'Sullivan, Ken Farion, Stan Matwin:
Engineering of a Clinical Decision Support Framework for the Point of Care Use. AMIA 2008 - [c79]Jiang Su, Harry Zhang, Charles X. Ling, Stan Matwin:
Discriminative parameter learning for Bayesian networks. ICML 2008: 1016-1023 - [c78]Sylvain Létourneau, Stan Matwin, A. Fazel Famili:
Generation of Globally Relevant Continuous Features for Classification. PAKDD 2008: 196-208 - [c77]Jin Huang, Charles X. Ling, Harry Zhang, Stan Matwin:
Proper Model Selection with Significance Test. ECML/PKDD (1) 2008: 536-547 - [p3]Justin Zhijun Zhan, LiWu Chang, Stan Matwin:
How to Prevent Private Data from being Disclosed to a Malicious Attacker. Data Mining: Foundations and Practice 2008: 517-528 - [p2]Justin Zhijun Zhan, Stan Matwin, LiWu Chang:
Privacy-Preserving Naive Bayesian Classification over Horizontally Partitioned Data. Data Mining: Foundations and Practice 2008: 529-538 - [e5]Aijun An, Stan Matwin, Zbigniew W. Ras, Dominik Slezak:
Foundations of Intelligent Systems, 17th International Symposium, ISMIS 2008, Toronto, Canada, May 20-23, 2008, Proceedings. Lecture Notes in Computer Science 4994, Springer 2008, ISBN 978-3-540-68122-9 [contents] - 2007
- [j31]Justin Zhijun Zhan, Stan Matwin, LiWu Chang:
Privacy-preserving multi-party decision tree induction. Int. J. Bus. Intell. Data Min. 2(2): 197-212 (2007) - [j30]Justin Zhijun Zhan, Stan Matwin:
Privacy-preserving support vector machine classification. Int. J. Intell. Inf. Database Syst. 1(3/4): 356-385 (2007) - [j29]Justin Zhijun Zhan, Stan Matwin:
Privacy-Preserving Data Mining in Electronic Surveys. Int. J. Netw. Secur. 4(3): 318-327 (2007) - [j28]Justin Zhijun Zhan, Stan Matwin, LiWu Chang:
Privacy-preserving collaborative association rule mining. J. Netw. Comput. Appl. 30(3): 1216-1227 (2007) - [c76]Dympna O'Sullivan, Ken Farion, Stan Matwin, Wojtek Michalowski, Szymon Wilk:
A Concept-Based Framework for Retrieving Evidence to Support Emergency Physician Decision Making at the Point of Care. K4CARE 2007: 117-126 - [c75]Venanzio Capretta, Bernard Stepien, Amy P. Felty, Stan Matwin:
Formal correctness of conflict detection for firewalls. FMSE 2007: 22-30 - [c74]Dympna O'Sullivan, William Elazmeh, Szymon Wilk, Ken Farion, Stan Matwin, Wojtek Michalowski, Morvarid Sehatkar:
Using Secondary Knowledge to Support Decision Tree Classification of Retrospective Clinical Data. MCD 2007: 238-251 - [e4]Joost N. Kok, Jacek Koronacki, Ramón López de Mántaras, Stan Matwin, Dunja Mladenic, Andrzej Skowron:
Machine Learning: ECML 2007, 18th European Conference on Machine Learning, Warsaw, Poland, September 17-21, 2007, Proceedings. Lecture Notes in Computer Science 4701, Springer 2007, ISBN 978-3-540-74957-8 [contents] - [e3]Joost N. Kok, Jacek Koronacki, Ramón López de Mántaras, Stan Matwin, Dunja Mladenic, Andrzej Skowron:
Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, Warsaw, Poland, September 17-21, 2007, Proceedings. Lecture Notes in Computer Science 4702, Springer 2007, ISBN 978-3-540-74975-2 [contents] - 2006
- [j27]Chris Drummond, Stan Matwin, Chad Gaffield:
Inferring and revising theories with confidence: analyzing bilingualism in the 1901 canadian census. Appl. Artif. Intell. 20(1): 1-33 (2006) - [j26]Jerffeson Teixeira de Souza, Stan Matwin, Nathalie Japkowicz:
Parallelizing Feature Selection. Algorithmica 45(3): 433-456 (2006) - [c73]David Nadeau, Peter D. Turney, Stan Matwin:
Unsupervised Named-Entity Recognition: Generating Gazetteers and Resolving Ambiguity. Canadian AI 2006: 266-277 - [c72]Maria Fernanda Caropreso, Stan Matwin:
Beyond the Bag of Words: A Text Representation for Sentence Selection. Canadian AI 2006: 324-335 - [c71]Svetlana Kiritchenko, Stan Matwin, Richard Nock, A. Fazel Famili:
Learning and Evaluation in the Presence of Class Hierarchies: Application to Text Categorization. Canadian AI 2006: 395-406 - [c70]William Elazmeh, Nathalie Japkowicz, Stan Matwin:
Evaluating Misclassifications in Imbalanced Data. ECML 2006: 126-137 - [c69]Justin Zhijun Zhan, Stan Matwin:
A Crypto-Based Approach to Privacy-Preserving Collaborative Data Mining. ICDM Workshops 2006: 546-550 - [c68]Justin Zhijun Zhan, Stan Matwin:
Privacy-Oriented Collaborative Learning Systems. SMC 2006: 4102-4105 - [p1]Justin Zhijun Zhan, LiWu Chang, Stan Matwin:
Privacy-Preserving Collaborative Data Mining. Foundations and Novel Approaches in Data Mining 2006: 213-227 - 2005
- [j25]Justin Zhijun Zhan, LiWu Chang, Stan Matwin:
Privacy Preserving K-nearest Neighbor Classification. Int. J. Netw. Secur. 1(1): 46-51 (2005) - [c67]Quintin Armour, William Elazmeh, Nour El-Kadri, Nathalie Japkowicz, Stan Matwin:
Privacy Compliance Enforcement in Email. Canadian AI 2005: 194-204 - [c66]Guillaume Dufay, Amy P. Felty, Stan Matwin:
Privacy-Sensitive Information Flow with JML. CADE 2005: 116-130 - [c65]Narjès Boufaden, William Elazmeh, Yimin Ma, Stan Matwin, Nour El-Kadri, Nathalie Japkowicz:
PEEP- An Information Extraction base approach for Privacy Protection in Email. CEAS 2005 - [c64]Justin Zhijun Zhan, Stan Matwin, LiWu Chang:
Privacy-Preserving Collaborative Association Rule Mining. DBSec 2005: 153-165 - [c63]Justin Zhijun Zhan, LiWu Chang, Stan Matwin:
Building k-nearest neighbor classifiers on vertically partitioned private data. GrC 2005: 708-711 - [c62]Justin Zhijun Zhan, Stan Matwin, LiWu Chang:
Private Mining of Association Rules. ISI 2005: 72-80 - [c61]Jerffeson Teixeira de Souza, Nathalie Japkowicz, Stan Matwin:
STochFS: A Framework for Combining Feature Selection Outcomes Through a Stochastic Process. PKDD 2005: 667-674 - [c60]Narjès Boufaden, William Elazmeh, Stan Matwin, Nathalie Japkowicz:
PEEP- Privacy Enforcement in Email Project. PST 2005 - [c59]Stan Matwin, Amy P. Felty, István T. Hernádvölgyi, Venanzio Capretta:
Privacy in Data Mining Using Formal Methods. TLCA 2005: 278-292 - 2004
- [j24]M. Ouerd, B. John Oommen, Stan Matwin:
A formal approach to using data distributions for building causal polytree structures. Inf. Sci. 168(1-4): 111-132 (2004) - [j23]Érick Alphonse, Stan Matwin:
Filtering Multi-Instance Problems to Reduce Dimensionality in Relational Learning. J. Intell. Inf. Syst. 22(1): 23-40 (2004) - [j22]Stan Matwin:
Guest Editorial. Mach. Learn. 57(3): 203-204 (2004) - [c58]Justin Zhijun Zhan, LiWu Chang, Stan Matwin:
Privacy-Preserving Multi-Party Decision Tree Induction. DBSec 2004: 341-355 - [c57]Justin Zhijun Zhan, LiWu Chang, Stan Matwin:
Bayesian Network Induction With Incomplete Private Data. ICEB 2004: 1119-1124 - [c56]Justin Zhijun Zhan, Stan Matwin, Nathalie Japkowicz, LiWu Chang:
Privacy-Preserving Collaborative Association Rule Mining. ICEB 2004: 1172-1178 - [c55]Justin Zhijun Zhan, Stan Matwin:
Privacy-Preserving Data Mining in Electronic Surveys. ICEB 2004: 1179-1185 - [c54]Svetlana Kiritchenko, Stan Matwin, Suhayya Abu-Hakima:
Email Classification with Temporal Features. Intelligent Information Systems 2004: 523-533 - [c53]Jelber Sayyad-Shirabad, Timothy C. Lethbridge, Stan Matwin:
Mining the Software Change Repository of a Legacy Telephony System. MSR 2004: 53-57 - [c52]Jelber Sayyad-Shirabad, Stan Matwin, Timothy C. Lethbridge:
Predictive Software Models. STEP 2004: 10-22 - 2003
- [c51]Marvin Zaluski, Nathalie Japkowicz, Stan Matwin:
Case Authoring from Text and Historical Experiences. AI 2003: 222-236 - [c50]Ouerd Messaouda, B. John Oommen, Stan Matwin:
Enhancing Caching in Distributed Databases Using Intelligent Polytree Representations. AI 2003: 498-504 - [c49]Jelber Sayyad-Shirabad, Timothy C. Lethbridge, Stan Matwin:
Applying data mining to software maintenance records. CASCON 2003: 253-265 - [c48]Jelber Sayyad-Shirabad, Timothy Lethbridge, Stan Matwin:
Mining the Maintenance History of a Legacy Software System. ICSM 2003: 95-104 - [e2]Stan Matwin, Claude Sammut:
Inductive Logic Programming, 12th International Conference, ILP 2002, Sydney, Australia, July 9-11, 2002. Revised Papers. Lecture Notes in Computer Science 2583, Springer 2003, ISBN 3-540-00567-6 [contents] - 2002
- [c47]Svetlana Kiritchenko, Stan Matwin:
Generalized Features: Their Application to Classification. AAAI/IAAI 2002: 985 - [c46]Érick Alphonse, Stan Matwin:
Feature Subset Selection and Inductive Logic Programming. ICML 2002: 11-18 - [c45]Érick Alphonse, Stan Matwin:
A Dynamic Approach to Dimensionality Reduction in Relational Learning. ISMIS 2002: 255-264 - [c44]Amy P. Felty, Stan Matwin:
Privacy-Oriented Data Mining by Proof Checking. PKDD 2002: 138-149 - [c43]Ouerd Messaouda, B. John Oommen, Stan Matwin:
Data generation for testing DAG-structured Bayesian networks. SMC 2002: 6 - 2001
- [j21]Johanne Morin, Stan Matwin:
GENEX: a tool for testing in ILP. Softw. Pract. Exp. 31(10): 1003-1023 (2001) - [c42]Svetlana Kiritchenko, Stan Matwin:
Email classification with co-training. CASCON 2001: 8 - [c41]Jelber Sayyad-Shirabad, Timothy Lethbridge, Stan Matwin:
Supporting Software Maintenance by Mining Software Update Records. ICSM 2001: 22-31 - [e1]Eleni Stroulia, Stan Matwin:
Advances in Artificial Intelligence, 14th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, AI 2001, Ottawa, Canada, June 7-9, 2001, Proceedings. Lecture Notes in Computer Science 2056, Springer 2001, ISBN 3-540-42144-0 [contents] - 2000
- [c40]Johanne Morin, Stan Matwin:
Relational Learning with Transfer of Knowledge Between Domains. AI 2000: 379-388 - [c39]Jelber Sayyad-Shirabad, Timothy C. Lethbridge, Stan Matwin:
Supporting maintenance of legacy software with data mining techniques. CASCON 2000: 11 - [c38]Gregory E. Kersten, Stan Matwin, Sunil J. Noronha, Mik Kersten:
The Software for Cultures and the Cultures in Software. ECIS 2000: 509-514 - [c37]Johanne Morin, Stan Matwin:
Learning Relational Clichés with Contextual LGG. ISMIS 2000: 274-282 - [c36]M. Ouerd, B. John Oommen, Stan Matwin:
A Formalism for Building Causal Polytree Structures Using Data Distributions. ISMIS 2000: 629-637
1990 – 1999
- 1999
- [j20]Sylvain Létourneau, Fazel Famili, Stan Matwin:
Data mining to predict aircraft component replacement. IEEE Intell. Syst. 14(6): 59-66 (1999) - [c35]Sam Scott, Stan Matwin:
Feature Engineering for Text Classification. ICML 1999: 379-388 - [c34]Mauricio Amaral de Almeida, Stan Matwin:
Machine Learning Method for Software Quality Model Building. ISMIS 1999: 565-573 - 1998
- [j19]Miroslav Kubat, Robert C. Holte, Stan Matwin:
Machine Learning for the Detection of Oil Spills in Satellite Radar Images. Mach. Learn. 30(2-3): 195-215 (1998) - [c33]Sylvain Delisle, Sylvain Létourneau, Stan Matwin:
Experiments with Learning Parsing Heuristics. COLING-ACL 1998: 307-314 - [c32]Riverson Rios, Stan Matwin:
Predicate Invention from a Few Examples. Canadian AI 1998: 455-466 - [c31]Sam Scott, Stan Matwin:
Text Classification Using WordNet Hypernyms. WordNet@ACL/COLING 1998 - [c30]Sylvain Létourneau, Stan Matwin, Fazel Famili:
A Normalization Method for Contextual Data: Experience from a Large-Scale Application. ECML 1998: 49-54 - 1997
- [j18]Peter Clark, Cao Feng, Stan Matwin, Ko Fung:
Improving Image Classification by Combining Statistical, Case-Based and Model Based Prediction Methods. Fundam. Informaticae 30(3/4): 227-240 (1997) - [c29]Miroslav Kubat, Robert C. Holte, Stan Matwin:
Learning When Negative Examples Abound. ECML 1997: 146-153 - [c28]Miroslav Kubat, Stan Matwin:
Addressing the Curse of Imbalanced Training Sets: One-Sided Selection. ICML 1997: 179-186 - 1996
- [c27]Daniel Charlebois, David G. Goodenough, Stan Matwin, A. S. (Pal) Bhogal, Hugh Barclay:
Planning and Learning in a Natural Resource Information System. AI 1996: 187-199 - [c26]Riverson Rios, Stan Matwin:
Efficient Induction of Recursive Prolog Definitons. AI 1996: 240-248 - 1995
- [j17]Cindy L. Mason, Stan Matwin:
Guest Editors' Introduction: Environmental Applications of AI. IEEE Expert 10(6): 12-13 (1995) - [j16]Stan Matwin, Daniel Charlebois, David G. Goodenough, A. S. (Pal) Bhogal:
Machine Learning and Planning for Data Management in Forestry. IEEE Expert 10(6): 35-40 (1995) - [c25]Xiaobin Li, Stan Szpakowicz, Stan Matwin:
A WordNet-based Algorithm for Word Sense Disambiguation. IJCAI 1995: 1368-1374 - 1994
- [j15]David G. Goodenough, Daniel Charlebois, Stan Matwin, Michael A. Robson:
Automating reuse of software for expert system analysis of remote sensing data. IEEE Trans. Geosci. Remote. Sens. 32(3): 525-533 (1994) - [c24]David W. Aha, Stephane Lapointe, Charles X. Ling, Stan Matwin:
Inverting Implication with Small Training Sets. ECML 1994: 31-48 - [c23]David W. Aha, Stephane Lapointe, Charles X. Ling, Stan Matwin:
Learning Recursive Relations with Randomly Selected Small Training Sets. ICML 1994: 12-18 - [c22]Stan Matwin, Affa Ahmad:
Reuse of Modular Software with Automated Comment Analysis. ICSM 1994: 222-231 - 1993
- [j14]Gilles Fouqué, Stan Matwin:
A Case-Based Approach to Software Reuse. J. Intell. Inf. Syst. 2(2): 165-197 (1993) - [c21]Peter Clark, Stan Matwin:
Learning Domain Theories using Abstract Beckground Knowledge. ECML 1993: 360-365 - [c20]Peter Clark, Stan Matwin:
Using Qualitative Models to Guide Inductive Learning. ICML 1993: 49-56 - [c19]R. Jetzelsperger, Stan Matwin, Franz Oppacher:
Enhancing Reuse of Smalltalk Methods by Conceptual Clustering. ICTAI 1993: 108-112 - [c18]Stephane Lapointe, Charles X. Ling, Stan Matwin:
Constructive Inductive Logic Programming. IJCAI 1993: 1030-1036 - 1992
- [c17]Stephane Lapointe, Stan Matwin:
Sub-unification: A Tool for Efficient Induction of Recursive Programs. ML 1992: 273-281 - [c16]Hamid Ould-Brahim, Stan Matwin:
Reusing database queries in analogical domains. KBSE 1992: 80-89 - [c15]Gilles Fouqué, Stan Matwin:
CAESAR: a system for case based software reuse. KBSE 1992: 90-99 - 1991
- [j13]Stan Matwin, Tomasz Szapiro, Karen Zita Haigh:
Genetic algorithms approach to a negotiation support system. IEEE Trans. Syst. Man Cybern. 21(1): 102-114 (1991) - [c14]Sylvain Delisle, Stan Matwin, Lionel Zupan:
Integrating EBL with automatic Text Analysis. EWSL 1991: 347 - [c13]Mary Gick, Stan Matwin:
The Importance of Causal Structure and Facts in Evaluating Explanations. ML 1991: 51-54 - [c12]Sylvain Delisle, Stan Matwin, Jiandong Wang, Lionel Zupan:
Explanation-based Learning Helps Acquire Knowledge from Natural Language Texts. ISMIS 1991: 326-337 - 1990
- [j12]C. Geldrez, Stan Matwin, Johanne Morin, Robert L. Probert:
An Application of Explanation-Based Learning to Protocol Conformance Testing. IEEE Expert 5(5): 45-60 (1990) - [j11]Patrick Constant, Stan Matwin, Franz Oppacher:
LEW: Learning by Watching. IEEE Trans. Pattern Anal. Mach. Intell. 12(3): 294-308 (1990) - [c11]Jean Genest, Stan Matwin, Boris Plante:
Explanation-Based Learning with Incomplete Theories: A Three-step Approach. ML 1990: 286-294
1980 – 1989
- 1989
- [j10]Stan Matwin, Franz Oppacher, Patrick Constant:
Knowledge acquisition by incremental learning from problem-solution pairs. Comput. Intell. 5: 58-66 (1989) - [j9]Stan Matwin, Stan Szpakowicz, Zbig Koperczak, Gregory E. Kersten, Wojtek Michalowski:
Negoplan: an expert system shell for negotiation support. IEEE Expert 4(4): 50-62 (1989) - [c10]Stan Matwin, Johanne Morin:
Learning Procedural Knowledge in the EBG Context. ML 1989: 197-199 - [c9]Stan Matwin, Stan Szpakowicz, Zbig Koperczak:
NEGOPLAN: An Inference-Based Negotiation Support Tool. IFIP Congress 1989: 679-685 - 1988
- [c8]Francesco Bergadano, Stan Matwin, Ryszard S. Michalski, Jianping Zhang:
Measuring Quality of Concept Descriptions. EWSL 1988: 1-14 - [c7]Francesco Bergadano, Stan Matwin, Ryszard S. Michalski, Jianping Zhang:
Representing and Acquiring Imprecise and Context-dependent Concepts in Knowledge-Based Systems. ISMIS 1988: 270-280 - [c6]Stan Matwin, Franz Oppacher:
Learning by Watching: An Incremental Machine Learning Method that Acquires Rules by Conceptual Clustering. ISMIS 1988: 363-373 - 1987
- [c5]Stan Matwin, Stan Szpakowicz, Gregory E. Kersten, Wojtek Michalowski, Zbig Koperczak:
A Logic-Based Tools for Negotiation Support. SLP 1987: 499-506 - 1986
- [j8]Kenneth Forsythe, Stan Matwin:
Copying of Dynamic Structures in a Pascal Environment. Softw. Pract. Exp. 16(4): 335-340 (1986) - 1985
- [j7]Stan Matwin, Tomasz Pietrzykowski:
Prograph: A Preliminary Report. Comput. Lang. 10(2): 91-126 (1985) - [j6]Douglas R. Skuce, Stan Matwin, Branka Tauzovich, Franz Oppacher, Stan Szpakowicz:
A Logic-Based Knowledge Source System for Natural Language Document. Data Knowl. Eng. 1(3): 201-231 (1985) - [j5]Stan Matwin, Tomasz Pietrzykowski:
Intelligent Backtracking in Plan-Based Deduction. IEEE Trans. Pattern Anal. Mach. Intell. 7(6): 682-692 (1985) - 1984
- [c4]Kenneth Forsythe, Stan Matwin:
Implementation Strategies for Plan-Based Deduction. CADE 1984: 426-444 - 1983
- [c3]Stan Matwin, Tomasz Pietrzykowski:
Intelligent Backtracking for Automated Deduction in FOL. Logic Programming Workshop 1983: 186-191 - 1982
- [c2]Tomasz Pietrzykowski, Stan Matwin:
Exponential Improvement of Efficient Backtracking: A Strategy for Plan-Based Deduction. CADE 1982: 223-239 - [c1]Stan Matwin, Tomasz Pietrzykowski:
Exponential Improvement of Efficient Backtracking: data Structure and Implementation. CADE 1982: 240-259
1970 – 1979
- 1978
- [j4]Michal Iglewski, Jan Madey, Stan Matwin:
A contribution to an improvement of PASCAL. ACM SIGPLAN Notices 13(1): 48-58 (1978) - 1977
- [j3]Stan Matwin:
On the Completeness of a Set of Transformations Optimizing Linear Programs. Inf. Process. Lett. 6(5): 165-167 (1977) - [j2]Stan Matwin:
An Experimental Investigation of Geschke's Method of Global Program Optimization. Inf. Process. Lett. 6(6): 177-179 (1977) - 1976
- [j1]Stan Matwin, Marek Missala:
A simple, machine independent tool for obtaining rough measures of PASCAL programs. ACM SIGPLAN Notices 11(8): 42-45 (1976)
Coauthor Index
[i51] [i50] [i48] [b1] [j79] [j76] [i43] [i42] [j71] [j70] [j67] [c216] [c213] [c212] [i41] [i39] [i38] [i37] [i36] [j64] [j63] [j61] [j60] [j59] [c211] [c209] [c206] [c205] [i33] [i32] [c202] [c201] [c199] [c198] [i29] [i28] [i27] [i25] [c192] [c191] [c190] [c189] [c185] [c183] [i14] [c176] [c175] [c172] [i10] [i9] [i7] [j52] [j45] [c139]
Bruno Brandoli Machado
aka: Bruno Brandoli
aka: Bruno Brandoli
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