MLSP-9.5
MATRIX DECOMPOSITION ON GRAPHS: A SIMPLIFIED FUNCTIONAL VIEW
Abhishek Sharma, Maks Ovsjanikov, Ecole Polytechnique, IP Paris, France
Session:
Matrix Factorization and Completion: Theory and Applications
Track:
Machine Learning for Signal Processing
Location:
Gather Area H
Presentation Time:
Sun, 8 May, 22:00 - 22:45 China Time (UTC +8)
Sun, 8 May, 14:00 - 14:45 UTC
Sun, 8 May, 14:00 - 14:45 UTC
Session Chair:
George Atia, University of Central Florida
Session MLSP-9
MLSP-9.1: MULTI-VIEW DATA REPRESENTATION VIA DEEP AUTOENCODER-LIKE NONNEGATIVE MATRIX FACTORIZATION
Haonan Huang, Yihao Luo, Guoxu Zhou, Qibin Zhao, Guangdong University of Technology, China
MLSP-9.2: ON IDENTIFIABLE POLYTOPE CHARACTERIZATION FOR POLYTOPIC MATRIX FACTORIZATION
Bariscan Bozkurt, Alper Erdogan, Koc University, Turkey
MLSP-9.3: FAST LEARNING OF FAST TRANSFORMS, WITH GUARANTEES
Quoc-Tung Le, Elisa Riccietti, Ecole normale supérieure de Lyon, France; Léon Zheng, valeo.ai, France; Rémi Gribonval, Inria, France
MLSP-9.4: REGRESSION ASSISTED MATRIX COMPLETION FOR RECONSTRUCTING A PROPAGATION FIELD WITH APPLICATION TO SOURCE LOCALIZATION
Hao Sun, Junting Chen, The Chinese University of Hong Kong(Shenzhen), China
MLSP-9.5: MATRIX DECOMPOSITION ON GRAPHS: A SIMPLIFIED FUNCTIONAL VIEW
Abhishek Sharma, Maks Ovsjanikov, Ecole Polytechnique, IP Paris, France
MLSP-9.6: Adversarially-Trained Nonnegative Matrix Factorization
Ting Cai, University of Wisconsin Madison, United States of America; Vincent Tan, National University of Singapore, Singapore; Cédric Févotte, Institut de Recherche en Informatique de Toulouse (IRIT), Université de Toulouse, France