L.10: Learning Theory I | |
Session Type: Lecture | |
Track: Statistics and Learning Theory | |
Virtual Session: View on Virtual Platform | |
Session Chair: Lizhong Zheng, Massachusetts Institute of Technology | |
L.10.1: On Estimation of Modal Decompositions | |
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Anuran Makur; Massachusetts Institute of Technology | |
Gregory W. Wornell; Massachusetts Institute of Technology | |
Lizhong Zheng; Massachusetts Institute of Technology | |
L.10.2: Robust Generalization via f-Mutual Information | |
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Amedeo Roberto Esposito; EPFL | |
Michael Gastpar; EPFL | |
Ibrahim Issa; American University of Beirut | |
L.10.3: Learning Representations by Maximizing Mutual Information in Variational Autoencoders | |
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Ali Lotfi Rezaabad; The University of Texas at Austin | |
Sriram Vishwanath; The University of Texas at Austin | |
L.10.4: Stochastic Bottleneck: Rateless Auto-Encoder for Flexible Dimensionality Reduction | |
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Toshiaki Koike-Akino; Mitsubishi Electric Research Laboratories (MERL) | |
Ye Wang; Mitsubishi Electric Research Laboratories (MERL) | |
L.10.5: Generalization Error Bounds via mth Central Moments of the Information Density | |
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Fredrik Hellström; Chalmers University of Technology | |
Giuseppe Durisi; Chalmers University of Technology | |
L.10.6: Exploring Unique Relevance for Mutual Information based Feature Selection | |
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Shiyu Liu; National University of Singapore | |
Mehul Motani; National University of Singapore | |
Plan Ahead
2021 IEEE International Symposium on Information Theory
11-16 July 2021 | Melbourne, Victoria, Australia