Learning, modeling and inference with data - I |
| Session Type: Lecture |
| Time: Tuesday, June 4, 10:00 - 12:00 |
| Location: Lecture Room 2 |
| Session Chair: Amir Leshem, Bar Ilan University |
| Paper #1: FINITE SAMPLE BOUNDS ON THE PERFORMANCE OF WEIGHTED LINEAR LEAST SQUARES IN SUB-GAUSSIAN CORRELATED NOISE |
| Michael Krikheli; Bar Ilan University |
| Amir Leshem; Bar Ilan University |
| Paper #2: ASYNCHRONOUS DISTRIBUTED EDGE-VARIANT GRAPH FILTERS |
| Mario Coutino; Delft University of Technology |
| Geert Leus; Delft University of Technology |
| Paper #3: LONG-RANGE DEPENDENCE PARAMETER ESTIMATION FOR MIXED SPECTRA GAUSSIAN PROCESSES |
| Lenin Arango Castillo; Queen's University |
| Glen Takahara; Queen's University |
| Paper #4: STRUCTURAL ROBUSTNESS FOR DEEP LEARNING ARCHITECTURES |
| Carlos Lassance; IMT Atlantique / Mila |
| Vincent Gripon; IMT Atlantique / Mila |
| Jian Tang; HEC / Mila |
| Antonio Ortega; University of Southern Califonia |
| Paper #5: BLIND ENSEMBLE CLASSIFICATION OF SEQUENTIAL DATA |
| Panagiotis Traganitis; University of Minnesota |
| Paper #6: ONLINE SELECTIVE TRAINING FOR FASTER NEURAL NETWORK LEARNING |
| Sara Mourad; University of Texas at Austin |
| Haris Vikalo; University of Texas at Austin |
| Ahmed Tewfik; University of Texas at Austin |