MLSP-51.3
RECOVERY OF NOISY POOLED TESTS VIA LEARNED FACTOR GRAPHS WITH APPLICATION TO COVID-19 TESTING
Eyal Fishel Ben-Knaan, Nir Shlezinger, Ben Gurion University, Israel; Yonina Eldar, Weizmann Institute of Science, Israel
Session:
Learning Theory and Algorithms III
Track:
Machine Learning for Signal Processing
Location:
Gather Area G
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:
Tommy Alstrøm, Technical University of Denmark
Session MLSP-51
MLSP-51.1: Graph Learning from Multivariate Dependent Time Series via a Multi-Attribute Formulation
Jitendra Tugnait, Auburn University, United States of America
MLSP-51.2: GENERALIZED SLICED PROBABILITY METRICS
Soheil Kolouri, Vanderbilt University, United States of America; Kimia Nadjahi, Telecom Paris, France; Shahin Shahrampour, Northeastern University, United States of America; Umut Simsekli, INRIA / ENS, France
MLSP-51.3: RECOVERY OF NOISY POOLED TESTS VIA LEARNED FACTOR GRAPHS WITH APPLICATION TO COVID-19 TESTING
Eyal Fishel Ben-Knaan, Nir Shlezinger, Ben Gurion University, Israel; Yonina Eldar, Weizmann Institute of Science, Israel
MLSP-51.4: A REMEDY FOR DISTRIBUTIONAL SHIFTS THROUGH EXPECTED DOMAIN TRANSLATION
Jean-Christophe Gagnon-Audet, Irina Rish, University of Montréal and Mila - Québec AI Institute, Canada; Soroosh Shahtalebi, Vector Institute for Artificial intelligence, Canada; Frank Rudzicz, University of Toronto and Vector Institute for Artificial intelligence, Canada
MLSP-51.5: DETERMINISTIC TRANSFORM BASED WEIGHT MATRICES FOR NEURAL NETWORKS
Pol Grau Jurado, Saikat Chatterjee, KTH Royal Institute of Technology, Sweden; Xinyue Liang, Ocean University of China, China
MLSP-51.6: ADAPTIVE GROUP TESTING WITH MISMATCHED MODELS
Mingzhou Fan, Byung-Jun Yoon, Edward R. Dougherty, Xiaoning Qian, Texas A&M University, United States of America; Francis Alexander, Brookhaven National Laboratory, United States of America