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ORCIDStan Matwin
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- affiliation: Dalhousie University, Nova Scotia, Canada
- affiliation (former): University of Ottawa, Ontario, Canada
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2020 – today
- 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- [j78]Noah Barrett, Zahra Sadeghi, Stan Matwin:
Evolutionary Augmentation Policy Optimization for Self-Supervised Learning. Adv. Artif. Intell. Mach. Learn. 3(2): 1135-1164 (2023) - [j77]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) - [j76]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) - [j75]Martha Dais Ferreira, Jessica 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) - [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) - [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) - [c214]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 - [c213]Lubna Eljabu, Mohammad Etemad, Stan Matwin:
Spatial Clustering Method of Historical AIS Data for Maritime Traffic Routes Extraction. IEEE Big Data 2022: 893-902 - [c212]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 - [c211]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 - [c210]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 Comandé, 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) - [c209]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 - [c208]Fatemeh Rahimi, Evangelos E. Milios, Stan Matwin:
MTLV: a library for building deep multi-task learning architectures. DocEng 2021: 8:1-8:4 - [c207]Fernando Henrique Oliveira Abreu, Amílcar Soares, Fernando V. Paulovich, Stan Matwin:
Local Anomaly Detection In Maritime Traffic Using Visual Analytics. EDBT/ICDT Workshops 2021 - [c206]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 - [c205]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 - [c204]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 - [c203]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 - [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 Comandé, 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) - [c202]Riccardo Guidotti, Anna Monreale, Stan Matwin, Dino Pedreschi:
Explaining Image Classifiers Generating Exemplars and Counter-Exemplars from Latent Representations. AAAI 2020: 13665-13668 - [c201]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 - [c200]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 - [c199]Gashin Ghazizadeh, Mirerfan Gheibi, Stan Matwin:
CB-DBSCAN: A Novel Clustering Algorithm for Adjacent Clusters with Different Densities. Canadian AI 2020: 232-237 - [c198]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 - [c197]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 - [c196]Xiang Jiang, Qicheng Lao, Stan Matwin, Mohammad Havaei:
Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation. ICML 2020: 4816-4827 - [c195]Habibeh Naderi, Behrouz Haji Soleimani, Stan Matwin:
Generating High-Fidelity Images with Disentangled Adversarial VAEs and Structure-Aware Loss. IJCNN 2020: 1-8 - [c194]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] - [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) - [c193]Behrouz Haji Soleimani, Stan Matwin:
Fast PMI-Based Word Embedding with Efficient Use of Unobserved Patterns. AAAI 2019: 7031-7038 - [c192]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 - [c191]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 - [c190]Mohammad Etemad, Amílcar Soares Júnior, Stan Matwin, Luís Torgo:
On Feature Selection and Evaluation of Transportation Mode Prediction Strategies. EDBT/ICDT Workshops 2019 - [c189]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 - [c188]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 - [c187]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 - [c186]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 - [c185]Xiang Jiang, Mohammad Havaei, Farshid Varno, Gabriel Chartrand, Nicolas Chapados, Stan Matwin:
Learning to Learn with Conditional Class Dependencies. ICLR (Poster) 2019 - [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]