Abstract:
The minimum error entropy (MEE) criterion is a powerful approach for non-Gaussian signal processing and robust machine learning. However, the instantiation of MEE on robu...Show MoreMetadata
Abstract:
The minimum error entropy (MEE) criterion is a powerful approach for non-Gaussian signal processing and robust machine learning. However, the instantiation of MEE on robust classification is a rather vacancy in the literature. The original MEE purely focuses on minimizing Renyi’s quadratic entropy of the prediction errors, which could exhibit inferior capability in noisy classification tasks. To this end, we analyze the optimal error distribution with adverse outliers and introduce a specific codebook for restriction, which optimizes the error distribution toward the optimal case. Half-quadratic-based optimization and convergence analysis of the proposed learning criterion, called restricted MEE (RMEE), are provided. The experimental results considering logistic regression and extreme learning machine on synthetic data and UCI datasets, respectively, are presented to demonstrate the superior robustness of RMEE. Furthermore, we evaluate RMEE on a noisy electroencephalogram dataset, so as to strengthen its practical impact.
Published in: IEEE Transactions on Neural Networks and Learning Systems ( Volume: 33, Issue: 11, November 2022)
Funding Agency:
Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Japan
Yuanhao Li received the B.S. degree from the Department of Automation Science and Technology, Xi’an Jiaotong University, Xi’an, China, in 2018. He is currently pursuing the Ph.D. degree with the Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Japan.
His current research focuses mainly on information-theoretic learning, robust machine learning, and their applications in advanced brain decoding alg...Show More
Yuanhao Li received the B.S. degree from the Department of Automation Science and Technology, Xi’an Jiaotong University, Xi’an, China, in 2018. He is currently pursuing the Ph.D. degree with the Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Japan.
His current research focuses mainly on information-theoretic learning, robust machine learning, and their applications in advanced brain decoding alg...View more
Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an, China
Badong Chen (Senior Member, IEEE) received the Ph.D. degree in computer science and technology from Tsinghua University, Beijing, China, in 2008.
He was a Post-Doctoral Associate with the Computational NeuroEngineering Laboratory, University of Florida, Gainesville, FL, USA, from 2010 to 2012. He is currently a Professor with the Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an, China. He...Show More
Badong Chen (Senior Member, IEEE) received the Ph.D. degree in computer science and technology from Tsinghua University, Beijing, China, in 2008.
He was a Post-Doctoral Associate with the Computational NeuroEngineering Laboratory, University of Florida, Gainesville, FL, USA, from 2010 to 2012. He is currently a Professor with the Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an, China. He...View more
Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Japan
Precursory Research for Embryonic Science and Technology (PRESTO), Japan Science and Technology Agency, Saitama, Japan
Natsue Yoshimura received the M.S. degree from Tokyo Medical and Dental University, Tokyo, Japan, in 2006, and the Ph.D. degree from The University of Electro-Communications, Chofu, Japan, in 2009.
She was a Post-Doctoral Researcher with the Tokyo Institute of Technology, Yokohama, Japan, from 2009 to 2010, where she became an Assistant Professor. She has been an Associate Professor with the Institute of Innovative Researc...Show More
Natsue Yoshimura received the M.S. degree from Tokyo Medical and Dental University, Tokyo, Japan, in 2006, and the Ph.D. degree from The University of Electro-Communications, Chofu, Japan, in 2009.
She was a Post-Doctoral Researcher with the Tokyo Institute of Technology, Yokohama, Japan, from 2009 to 2010, where she became an Assistant Professor. She has been an Associate Professor with the Institute of Innovative Researc...View more
Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Japan
Yasuharu Koike received the B.S., M.S., and Ph.D. degrees in engineering from the Tokyo Institute of Technology, Tokyo, Japan, in 1987, 1989, and 1996, respectively.
From 1989 to 1998, he was with Toyota Motor Corporation, Nagoya, Japan. From 1991 to 1994, he transferred to the Advanced Tele-Communications Research Human Information Processing Laboratories, Kyoto, Japan. In 1998, he moved to the Precision and Intelligence ...Show More
Yasuharu Koike received the B.S., M.S., and Ph.D. degrees in engineering from the Tokyo Institute of Technology, Tokyo, Japan, in 1987, 1989, and 1996, respectively.
From 1989 to 1998, he was with Toyota Motor Corporation, Nagoya, Japan. From 1991 to 1994, he transferred to the Advanced Tele-Communications Research Human Information Processing Laboratories, Kyoto, Japan. In 1998, he moved to the Precision and Intelligence ...View more
Contents Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Japan
Yuanhao Li received the B.S. degree from the Department of Automation Science and Technology, Xi’an Jiaotong University, Xi’an, China, in 2018. He is currently pursuing the Ph.D. degree with the Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Japan.
His current research focuses mainly on information-theoretic learning, robust machine learning, and their applications in advanced brain decoding algorithms for brain–computer interface.
Yuanhao Li received the B.S. degree from the Department of Automation Science and Technology, Xi’an Jiaotong University, Xi’an, China, in 2018. He is currently pursuing the Ph.D. degree with the Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Japan.
His current research focuses mainly on information-theoretic learning, robust machine learning, and their applications in advanced brain decoding algorithms for brain–computer interface.View more
Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an, China
Badong Chen (Senior Member, IEEE) received the Ph.D. degree in computer science and technology from Tsinghua University, Beijing, China, in 2008.
He was a Post-Doctoral Associate with the Computational NeuroEngineering Laboratory, University of Florida, Gainesville, FL, USA, from 2010 to 2012. He is currently a Professor with the Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an, China. He has authored or coauthored over 200 articles in various journals and conference proceedings. His research interests are in signal processing, machine learning, and their applications to neural engineering and robotics.
Dr. Chen serves (or has served) as a Technical Committee Member of the IEEE SPS Machine Learning for Signal Processing (MLSP) and the IEEE CIS Cognitive and Developmental Systems (CDS) and an Associate Editor (or an Editor Board Member) for seven international journals, including IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Cognitive and Developmental Systems, Neural Networks, Journal of The Franklin Institute, and Entropy.
Badong Chen (Senior Member, IEEE) received the Ph.D. degree in computer science and technology from Tsinghua University, Beijing, China, in 2008.
He was a Post-Doctoral Associate with the Computational NeuroEngineering Laboratory, University of Florida, Gainesville, FL, USA, from 2010 to 2012. He is currently a Professor with the Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an, China. He has authored or coauthored over 200 articles in various journals and conference proceedings. His research interests are in signal processing, machine learning, and their applications to neural engineering and robotics.
Dr. Chen serves (or has served) as a Technical Committee Member of the IEEE SPS Machine Learning for Signal Processing (MLSP) and the IEEE CIS Cognitive and Developmental Systems (CDS) and an Associate Editor (or an Editor Board Member) for seven international journals, including IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Cognitive and Developmental Systems, Neural Networks, Journal of The Franklin Institute, and Entropy.View more
Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Japan
Precursory Research for Embryonic Science and Technology (PRESTO), Japan Science and Technology Agency, Saitama, Japan
Natsue Yoshimura received the M.S. degree from Tokyo Medical and Dental University, Tokyo, Japan, in 2006, and the Ph.D. degree from The University of Electro-Communications, Chofu, Japan, in 2009.
She was a Post-Doctoral Researcher with the Tokyo Institute of Technology, Yokohama, Japan, from 2009 to 2010, where she became an Assistant Professor. She has been an Associate Professor with the Institute of Innovative Research, Tokyo Institute of Technology, since 2015. Her research interests include brain–machine/–computer interfaces and brain activity information decoding relating to motor control, speech, and emotion, using noninvasive brain activity recording methods, such as electroencephalography and functional magnetic resonance imaging.
Dr. Yoshimura is also a member of the Society for Neuroscience, the Japan Neuroscience Society, and the Japanese Society for Medical and Biological Engineering.
Natsue Yoshimura received the M.S. degree from Tokyo Medical and Dental University, Tokyo, Japan, in 2006, and the Ph.D. degree from The University of Electro-Communications, Chofu, Japan, in 2009.
She was a Post-Doctoral Researcher with the Tokyo Institute of Technology, Yokohama, Japan, from 2009 to 2010, where she became an Assistant Professor. She has been an Associate Professor with the Institute of Innovative Research, Tokyo Institute of Technology, since 2015. Her research interests include brain–machine/–computer interfaces and brain activity information decoding relating to motor control, speech, and emotion, using noninvasive brain activity recording methods, such as electroencephalography and functional magnetic resonance imaging.
Dr. Yoshimura is also a member of the Society for Neuroscience, the Japan Neuroscience Society, and the Japanese Society for Medical and Biological Engineering.View more
Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Japan
Yasuharu Koike received the B.S., M.S., and Ph.D. degrees in engineering from the Tokyo Institute of Technology, Tokyo, Japan, in 1987, 1989, and 1996, respectively.
From 1989 to 1998, he was with Toyota Motor Corporation, Nagoya, Japan. From 1991 to 1994, he transferred to the Advanced Tele-Communications Research Human Information Processing Laboratories, Kyoto, Japan. In 1998, he moved to the Precision and Intelligence Laboratory, Tokyo Institute of Technology, where he is currently a Professor with the Institute of Innovative Research. He was a Researcher of the precursory research for embryonic science and technology with Japan Science and Technology Corporation, Saitama, Japan, from 2000 to 2004 and Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency (JST), Saitama, from 2004 to 2014. His research interests include human motor control theory, human interface, and brain–machine interface and their applications.
Dr. Koike is also a member of the Society for Neuroscience, the Institute of Electronics, Information and Communication Engineers (IEICE), the Virtual Reality Society of Japan, and the Japan Neuroscience Society.
Yasuharu Koike received the B.S., M.S., and Ph.D. degrees in engineering from the Tokyo Institute of Technology, Tokyo, Japan, in 1987, 1989, and 1996, respectively.
From 1989 to 1998, he was with Toyota Motor Corporation, Nagoya, Japan. From 1991 to 1994, he transferred to the Advanced Tele-Communications Research Human Information Processing Laboratories, Kyoto, Japan. In 1998, he moved to the Precision and Intelligence Laboratory, Tokyo Institute of Technology, where he is currently a Professor with the Institute of Innovative Research. He was a Researcher of the precursory research for embryonic science and technology with Japan Science and Technology Corporation, Saitama, Japan, from 2000 to 2004 and Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency (JST), Saitama, from 2004 to 2014. His research interests include human motor control theory, human interface, and brain–machine interface and their applications.
Dr. Koike is also a member of the Society for Neuroscience, the Institute of Electronics, Information and Communication Engineers (IEICE), the Virtual Reality Society of Japan, and the Japan Neuroscience Society.View more
