SPTM-6.1
DECENTRALIZED BILEVEL OPTIMIZATION FOR PERSONALIZED CLIENT LEARNING
Songtao Lu, Xiaodong Cui, Mark Squillante, Brian Kingsbury, Lior Horesh, IBM Thomas J. Watson Research Center, United States of America
Session:
Optimization Methods for Signal Processing II
Track:
Signal Processing Theory and Methods
Location:
Gather Area M
Presentation Time:
Mon, 9 May, 21:00 - 21:45 China Time (UTC +8)
Mon, 9 May, 13:00 - 13:45 UTC
Mon, 9 May, 13:00 - 13:45 UTC
Session Chair:
Selin Aviente, Michigan State University
Session SPTM-6
SPTM-6.1: DECENTRALIZED BILEVEL OPTIMIZATION FOR PERSONALIZED CLIENT LEARNING
Songtao Lu, Xiaodong Cui, Mark Squillante, Brian Kingsbury, Lior Horesh, IBM Thomas J. Watson Research Center, United States of America
SPTM-6.2: Compressed Super-Resolution of Positive Sources
Maxime Ferreira Da Costa, University of Southern California, United States of America; Yuejie Chi, Carnegie Mellon University, United States of America
SPTM-6.3: EXTREME-POINT PURSUIT FOR UNIT-MODULUS OPTIMIZATION
Mingjie Shao, Qi Dai, Wing-Kin Ma, The Chinese University of Hong Kong, China
SPTM-6.4: GENERALIZED MATCHING PURSUITS FOR THE SPARSE OPTIMIZATION OF SEPARABLE OBJECTIVES
Sebastian Ament, Carla Gomes, Cornell University, United States of America
SPTM-6.5: EPIGRAPHICAL RELAXATION FOR MINIMIZING LAYERED MIXED NORMS
Seisuke Kyochi, Kogakuin University, Japan; Shunsuke Ono, Tokyo Institute of Technology, Japan; Ivan Selesnick, New York University, United States of America
SPTM-6.6: DELTA DISTANCING: A LIFTING APPROACH TO LOCALIZING ITEMS FROM USER COMPARISONS
Andrew McRae, Austin Xu, Jihui Jin, Namrata Nadagouda, Nauman Ahad, Peimeng Guan, Mark Davenport, Georgia Institute of Technology, United States of America; Santhosh Karnik, Michigan State University, United States of America