SPTM-11.2
DECENTRALIZED LEARNING IN THE PRESENCE OF LOW-RANK NOISE
Roula Nassif, Université Côte d'Azur, France; Virginia Bordignon, Ali Sayed, Ecole Polytechnique Fédérale de Lausanne, Switzerland; Stefan Vlaski, Imperial College London, United Kingdom of Great Britain and Northern Ireland
Session:
Adaptive Signal Processing
Track:
Signal Processing Theory and Methods
Location:
Gather Area M
Presentation Time:
Tue, 10 May, 22:00 - 22:45 China Time (UTC +8)
Tue, 10 May, 14:00 - 14:45 UTC
Tue, 10 May, 14:00 - 14:45 UTC
Session Chair:
Constantin Paleologu, University Politehnica of Bucharest
Session SPTM-11
SPTM-11.1: LMS AND NLMS ALGORITHMS FOR THE IDENTIFICATION OF IMPULSE RESPONSES WITH INTRINSIC SYMMETRIC OR ANTISYMMETRIC PROPERTIES
Jacob Benesty, INRS-EMT, University of Quebec, Canada; Constantin Paleologu, Silviu Ciochina, University Politehnica of Bucharest, Romania; Eduardo Vinicius Kuhn, Khaled Jamal Bakri, Rui Seara, Federal University of Santa Catarina, Brazil
SPTM-11.2: DECENTRALIZED LEARNING IN THE PRESENCE OF LOW-RANK NOISE
Roula Nassif, Université Côte d'Azur, France; Virginia Bordignon, Ali Sayed, Ecole Polytechnique Fédérale de Lausanne, Switzerland; Stefan Vlaski, Imperial College London, United Kingdom of Great Britain and Northern Ireland
SPTM-11.3: ADAPTIVE DIFFUSION WITH COMPRESSED COMMUNICATION
Marco Carpentiero, Vincenzo Matta, University of Salerno, Italy; Ali H. Sayed, École Polytechnique Fédérale de Lausanne, Switzerland
SPTM-11.4: JOINT CENTRALITY ESTIMATION AND GRAPH IDENTIFICATION FROM MIXTURE OF LOW PASS GRAPH SIGNALS
Yiran He, Hoi-To Wai, The Chinese University of Hong Kong, Hong Kong
SPTM-11.5: FAIRNESS-AWARE SELECTIVE SAMPLING ON ATTRIBUTED GRAPHS
Oyku Kose, Yanning Shen, University of California, Irvine, United States of America
SPTM-11.6: A SIMPLE GRAPH NEURAL NETWORK VIA LAYER SNIFFER
Dingyi Zeng, Li Zhou, Wanlong Liu, Hong Qu, Wenyu Chen, University of Electronic Science and Technology of China, China