SPTM-22.2
ECO-FEDSPLIT: FEDERATED LEARNING WITH ERROR-COMPENSATED COMPRESSION
Sarit Khirirat, Division of Decision and Control Systems, KTH Royal Institute of Technology, Sweden, Sweden; Sindri Magnússon, Stockholm University, Sweden; Mikael Johansson, KTH Royal Institute of Technology, Sweden
Session:
Signal Processing over Networks
Track:
Signal Processing Theory and Methods
Location:
Gather Area M
Presentation Time:
Fri, 13 May, 21:00 - 21:45 China Time (UTC +8)
Fri, 13 May, 13:00 - 13:45 UTC
Fri, 13 May, 13:00 - 13:45 UTC
Session Chair:
Yuejie Chi, Carnegie Mellon University
Session SPTM-22
SPTM-22.1: PRIVACY-PRESERVING FEDERATED MULTI-TASK LINEAR REGRESSION: A ONE-SHOT LINEAR MIXING APPROACH INSPIRED BY GRAPH REGULARIZATION
Harlin Lee, Andrea Bertozzi, University of California, Los Angeles, United States of America; Jelena Kovačević, New York University, United States of America; Yuejie Chi, Carnegie Mellon University, United States of America
SPTM-22.2: ECO-FEDSPLIT: FEDERATED LEARNING WITH ERROR-COMPENSATED COMPRESSION
Sarit Khirirat, Division of Decision and Control Systems, KTH Royal Institute of Technology, Sweden, Sweden; Sindri Magnússon, Stockholm University, Sweden; Mikael Johansson, KTH Royal Institute of Technology, Sweden
SPTM-22.3: A TIME ENCODING APPROACH TO TRAINING SPIKING NEURAL NETWORKS
Karen Adam, Ecole Polytechnique Fédérale de Lausanne, Switzerland
SPTM-22.4: TRANSIENT ANALYSIS OF CLUSTERED MULTITASK DIFFUSION RLS ALGORITHM
Wei Gao, Jiangsu University, China; Jie Chen, Wentao Shi, Qunfei Zhang, Northwestern Polytechnical University, China; Cedric Richard, Université Côte d’Azur, France
SPTM-22.5: IMPROVING INFERENCE FOR SPATIAL SIGNALS BY CONTEXTUAL FALSE DISCOVERY RATES
Martin Gölz, Abdelhak M. Zoubir, Technische Universität Darmstadt, Germany; Visa Koivunen, Aalto University, Finland
SPTM-22.6: ESTIMATION OF THE ADMITTANCE MATRIX IN POWER SYSTEMS UNDER LAPLACIAN AND PHYSICAL CONSTRAINTS
Morad Halihal, Tirza Routtenberg, Ben Gurion University of the Negev, Israel