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TU2.I: Adaptation and Learning over Graphs

Session Type: Poster
Time: Tuesday, 5 May, 16:30 - 18:30
Location: On-Demand
Session Chair: Geert Leus, TU Delft
 
   TU2.I.1: ADAPTATION AND LEARNING IN MULTI-TASK DECISION SYSTEMS
         Stefano Marano; university of salerno
         Ali H. Sayed; Ecole Polytechnique Fédérale de Lausanne (EPFL)
 
   TU2.I.2: GRAPH METRIC LEARNING VIA GERSHGORIN DISC ALIGNMENT
         Cheng Yang; York University
         Gene Cheung; York University
         Wei Hu; Peking University
 
   TU2.I.3: LEARNING GRAPH INFLUENCE FROM SOCIAL INTERACTIONS
         Vincenzo Matta; University of Salerno
         Virginia Bordignon; Ecole Polytechnique Fédérale de Lausanne (EPFL)
         Augusto Santos; [None]
         Ali H. Sayed; Ecole Polytechnique Fédérale de Lausanne (EPFL)
 
   TU2.I.4: SOCIAL LEARNING WITH PARTIAL INFORMATION SHARING
         Virginia Bordignon; Ecole Polytechnique Fédérale de Lausanne (EPFL)
         Vincenzo Matta; University of Salerno
         Ali H. Sayed; Ecole Polytechnique Fédérale de Lausanne (EPFL)
 
   TU2.I.5: NON-PARAMETRIC COMMUNITY CHANGE-POINTS DETECTION IN STREAMING GRAPH SIGNALS
         André Ferrari; Université Côte d'Azur
         Cédric Richard; Université Côte d'Azur
 
   TU2.I.6: SPATIAL GATING STRATEGIES FOR GRAPH RECURRENT NEURAL NETWORKS
         Luana Ruiz; University of Pennsylvania
         Fernando Gama; University of Pennsylvania
         Alejandro Ribeiro; University of Pennsylvania
 
   TU2.I.7: LEARNING CONNECTIVITY AND HIGHER-ORDER INTERACTIONS IN RADIAL DISTRIBUTION GRIDS
         Qiuling Yang; Beijing Institute of Technology
         Mario Coutino; Delft University of Technology
         Gang Wang; University of Minnesota
         Georgios B. Giannakis; University of Minnesota
         Geert Leus; Delft University of Technology
 
   TU2.I.8: SEMI-SUPERVISED LEARNING OF PROCESSES OVER MULTI-RELATIONAL GRAPHS
         Qin Lu; University of Minnesota
         Vassilis N. Ioannidis; University of Minnesota
         Georgios B. Giannakis; University of Minnesota
 
   TU2.I.9: RECURSIVE PREDICTION OF GRAPH SIGNALS WITH INCOMING NODES
         Arun Venkitaraman; KTH Royal Institute of Technology
         Saikat Chatterjee; KTH Royal Institute of Technology
         Bo Wahlberg; KTH Royal Institute of Technology
 
   TU2.I.10: LEARNING SIGNED GRAPHS FROM DATA
         Gerald Matz; Technische Universität Wien
         Thomas Dittrich; Technische Universität Wien
 
   TU2.I.11: FORECASTING MULTI-DIMENSIONAL PROCESSES OVER GRAPHS
         Alberto Natali; Delft University of Technology
         Elvin Isufi; Delft University of Technology
         Geert Leus; Delft University of Technology
 
  TU2.I.12: A REGULARIZATION FRAMEWORK FOR LEARNING OVER MULTITASK GRAPHS
         Roula Nassif; American University of Beirut
         Stefan Vlaski; Ecole Polytechnique Fédérale de Lausanne (EPFL)
         Cédric Richard; Universite de Nice Sophia-Antipolis
         Ali H. Sayed; Ecole Polytechnique Fédérale de Lausanne (EPFL)