TM1: Learning over Graphs |
| Session Type: Lecture |
| Time: Tuesday, December 17, 10:20 - 12:20 |
| Location: Salle Fort Royal |
| Session Chairs: Santiago Segarra, Rice University and Mario Coutino, TU Delft |
| TM1.1: LEARNING SPARSE HYPERGRAPHS FROM DYADIC RELATIONAL DATA |
| Mario Coutino, TU Delft, Netherlands; Sundeep Chepuri, Indian Institute of Science, India; Geert Leus, TU Delft, Netherlands |
| TM1.2: GRAPH NEURAL NETWORKS FOR PREDICTING PROTEIN FUNCTIONS |
| Vassilis N. Ioannidis, University of Minnesota, United States; Antonio G. Marques, King Juan Carlos University, Spain; Georgios B. Giannakis, University of Minnesota, United States |
| TM1.3: ONLINE NETWORK TOPOLOGY INFERENCE WITH PARTIAL CONNECTIVITY INFORMATION |
| Rasoul Shafipour, Gonzalo Mateos, University of Rochester, United States |
| TM1.4: AN UNDERPARAMETRIZED DEEP DECODER ARCHITECTURE FOR GRAPH SIGNALS |
| Samuel Rey, Antonio G. Marques, King Juan Carlos University, Spain; Santiago Segarra, Rice University, United States |
| TM1.5: A BLOCK COORDINATE DESCENT ALGORITHM FOR SPARSE GAUSSIAN GRAPHICAL MODEL INFERENCE WITH LAPLACIAN CONSTRAINTS |
| Tianyi Liu, Minh Trinh Hoang, Technische Universität Darmstadt, Germany; Yang Yang, Fraunhofer, Germany; Marius Pesavento, Technische Universität Darmstadt, Germany |
| TM1.6: SCALABLE AND ADAPTIVE KNN FOR REGRESSION OVER GRAPHS |
| Seth Barrash, University of Minnesota, Twin Cities, United States; Yanning Shen, University of California, Irvine, United States; Georgios B. Giannakis, University of Minnesota, United States |