Technical Program

TA1: Large Random Matrix Theory in Signal Processing and Machine Learning

Session Type: Lecture
Time: Tuesday, December 17, 17:45 - 19:45
Location: Salle Fort Royal
Session Chair: Nicolas Gillis, University of Mons
 
TA1.1: PHASE TRANSITIONS IN THE DYNAMIC MODE DECOMPOSITION ALGORITHM
Arvind Prasadan, Asad Lodhia, Raj Rao Nadakuditi, University of Michigan, United States
 
TA1.2: A RANDOM MATRIX ANALYSIS AND OPTIMIZATION FRAMEWORK TO LARGE DIMENSIONAL TRANSFER LEARNING
Romain Couillet, GIPSA-lab, University of Grenoble-Alpes, France
 
TA1.3: PERFORMANCE ANALYSIS OF A LOW-RANK DETECTOR UNDER TRAINING DATA CONTAMINATION
Pascal Vallet, Bordeaux INP, France; Guillaume Ginolhac, Polytech Annecy-Chambéry, France; Frédéric Pascal, CentraleSupélec, France; Philippe Forster, Université Paris-Nanterre, France
 
TA1.4: PROBABILITY OF RESOLUTION OF PARTIALLY RELAXED DML AN ASYMPTOTIC APPROACH
David Schenck, Technische Universität Darmstadt, Germany; Xavier Mestre, Centre Tecnològic de Telecomunicacions de Catalunya, Spain; Marius Pesavento, Technische Universität Darmstadt, Germany
 
TA1.5: PHASE TRANSITION IN THE HARD-MARGIN SUPPORT VECTOR MACHINES
Houssem Sifaou, Abla Kammoun, Mohamed-Slim Alouini, King Abdullah University of Science and Technology, Saudi Arabia
 
TA1.6: HIGH DIMENSIONAL ROBUST CLASSIFICATION: A RANDOM MATRIX ANALYSIS
Romain Couillet, GIPSA-lab, University of Grenoble-Alpes, France