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ORCIDTomasz Maszczyk
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2020 – today
- 2023
[j1]Farzam Farbiz
, Mohamed Salahuddin Habibullah, Brahim Hamadicharef, Tomasz Maszczyk, Saurabh Aggarwal:
Knowledge-embedded machine learning and its applications in smart manufacturing. J. Intell. Manuf. 34(7): 2889-2906 (2023)- 2020
- [c26]Tien-Dung Nguyen, Tomasz Maszczyk, Katarzyna Musial, Marc-André Zöller, Bogdan Gabrys:
AVATAR - Machine Learning Pipeline Evaluation Using Surrogate Model. IDA 2020: 352-365 - [i2]Tien-Dung Nguyen, Tomasz Maszczyk, Katarzyna Musial, Marc-André Zöller, Bogdan Gabrys:
AVATAR - Machine Learning Pipeline Evaluation Using Surrogate Model. CoRR abs/2001.11158 (2020)
2010 – 2019
- 2019
- [i1]Tomasz Maszczyk, Wlodzislaw Duch:
Support Feature Machines. CoRR abs/1901.09643 (2019) - 2018
- [c25]Subhasree Basu, Yi Han Victoria Chua, Mei Wah Lee, Wanyu Geraldine Lim, Tomasz Maszczyk, Zheng Guo, Justin Dauwels:
Towards a data-driven behavioral approach to prediction of insider-threat. IEEE BigData 2018: 4994-5001 - [c24]Debsubhra Chakraborty, Zixu Yang, Yasir Tahir, Tomasz Maszczyk, Justin Dauwels, Nadia Magnenat-Thalmann, Jianmin Zheng, Yogeswary Maniam, Nur Amirah, Bhing-Leet Tan, Jimmy Lee:
Prediction of Negative Symptoms of Schizophrenia from Emotion Related Low-Level Speech Signals. ICASSP 2018: 6024-6028 - [c23]Shihao Xu, Zixu Yang, Debsubhra Chakraborty, Yasir Tahir, Tomasz Maszczyk, Yi Han Victoria Chua, Justin Dauwels, Daniel Thalmann, Nadia Magnenat-Thalmann, Bhing-Leet Tan, Jimmy Chee Keong Lee:
Automatic Verbal Analysis of Interviews with Schizophrenic Patients. DSP 2018: 1-5 - [c22]Anusha James, Yi Han Victoria Chua, Tomasz Maszczyk, Ana Moreno Núñez, Rebecca Bull, Kerry Lee, Justin Dauwels:
Automated Classification of Classroom Climate by Audio Analysis. IWSDS 2018: 41-49 - [c21]Shihao Xu, Zixu Yang, Debsubhra Chakraborty, Yasir Tahir, Tomasz Maszczyk, Yi Han Victoria Chua, Justin Dauwels, Daniel Thalmann, Nadia Magnenat-Thalmann, Bhing-Leet Tan, Jimmy Chee Keong Lee:
Automated Lexical Analysis of Interviews with Individuals with Schizophrenia. IWSDS 2018: 185-197 - [c20]Anusha James, Mohan Kashyap, Yi Han Victoria Chua, Tomasz Maszczyk, Ana Moreno Núñez, Rebecca Bull, Justin Dauwels:
Inferring the Climate in Classrooms from Audio and Video Recordings: A Machine Learning Approach. TALE 2018: 983-988 - 2017
- [c19]Debsubhra Chakraborty, Yasir Tahir, Zixu Yang, Tomasz Maszczyk, Justin Dauwels, Daniel Thalmann, Nadia Magnenat-Thalmann, Bhing-Leet Tan, Jimmy Lee:
Assessment and prediction of negative symptoms of schizophrenia from RGB+D movement signals. MMSP 2017: 1-6 - [c18]John Thomas, Tomasz Maszczyk, Nishant Sinha, Tilmann Kluge, Justin Dauwels:
Deep learning-based classification for brain-computer interfaces. SMC 2017: 234-239 - 2016
- [c17]Alexander Rosenberg Johansen, Jing Jin, Tomasz Maszczyk, Justin Dauwels, Sydney S. Cash, M. Brandon Westover:
Epileptiform spike detection via convolutional neural networks. ICASSP 2016: 754-758 - [c16]Apratim Choudhury, Tomasz Maszczyk, Justin Dauwels, Chetan Belagal Math, Hong Li:
An Integrated Simulation Environment for Testing V2X Protocols and Applications. ICCS 2016: 2042-2052 - [c15]Apratim Choudhury, Tomasz Maszczyk, Muhammad Tayyab Asif, Nikola Mitrovic, Chetan Belagal Math, Hong Li, Justin Dauwels:
An integrated V2X simulator with applications in vehicle platooning. ITSC 2016: 1017-1022 - [c14]Nishant Sinha, Tomasz Maszczyk, Zhang Wanxuan, Jonathan Tan, Justin Dauwels:
EEG hyperscanning study of inter-brain synchrony during cooperative and competitive interaction. SMC 2016: 4813-4818 - 2015
- [c13]Yasir Tahir, Debsubhra Chakraborty, Tomasz Maszczyk, Shoko Dauwels, Justin Dauwels, Nadia Magnenat-Thalmann, Daniel Thalmann:
Real-time sociometrics from audio-visual features for two-person dialogs. DSP 2015: 823-827 - 2012
- [c12]Tomasz Maszczyk, Wlodzislaw Duch:
Locally Optimized Kernels. ICAISC (1) 2012: 412-420 - [c11]Marcin Blachnik, Wlodzislaw Duch, Tomasz Maszczyk:
Feature Ranking Methods Used for Selection of Prototypes. ICANN (2) 2012: 296-304 - [c10]Tomasz Maszczyk, Wlodzislaw Duch:
Recursive Similarity-Based Algorithm for Deep Learning. ICONIP (3) 2012: 390-397 - [c9]Wlodzislaw Duch, Norbert Jankowski, Tomasz Maszczyk:
Make it cheap: Learning with O(nd) complexity. IJCNN 2012: 1-4 - 2011
- [p2]Wlodzislaw Duch, Tomasz Maszczyk, Marek Grochowski:
Optimal Support Features for Meta-Learning. Meta-Learning in Computational Intelligence 2011: 317-358 - 2010
- [c8]Tomasz Maszczyk, Wlodzislaw Duch:
Triangular Visualization. ICAISC (1) 2010: 445-452 - [c7]Tomasz Maszczyk, Wlodzislaw Duch:
Almost Random Projection Machine with Margin Maximization and Kernel Features. ICANN (2) 2010: 40-48 - [c6]Tomasz Maszczyk, Wlodzislaw Duch:
Support Feature Machines: Support vectors are not enough. IJCNN 2010: 1-8 - [c5]Tomasz Maszczyk, Wlodzislaw Duch:
Support Feature Machine for DNA Microarray Data. RSCTC 2010: 178-186 - [p1]Tomasz Maszczyk, Marek Grochowski, Wlodzislaw Duch:
Discovering Data Structures Using Meta-learning, Visualization and Constructive Neural Networks. Advances in Machine Learning II 2010: 467-484
2000 – 2009
- 2009
- [c4]Wlodzislaw Duch, Tomasz Maszczyk:
Almost Random Projection Machine. ICANN (1) 2009: 789-798 - [c3]Wlodzislaw Duch, Tomasz Maszczyk:
Universal Learning Machines. ICONIP (2) 2009: 206-215 - 2008
- [c2]Tomasz Maszczyk, Wlodzislaw Duch:
Comparison of Shannon, Renyi and Tsallis Entropy Used in Decision Trees. ICAISC 2008: 643-651 - [c1]Tomasz Maszczyk, Wlodzislaw Duch:
Support Vector Machines for Visualization and Dimensionality Reduction. ICANN (1) 2008: 346-356
Coauthor Index
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last updated on 2024-08-05 21:14 CEST by the dblp team
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