Nonconvex Optimization for Data Science |
| Session Type: Lecture |
| Time: Tuesday, June 4, 16:20 - 18:00 |
| Location: Lecture Room 1 |
| Session Chairs: Mingyi Hong, University of Minnesota and Mingyi Hong, University of Minnesota |
| Paper #1: GNSD: A GRADIENT-TRACKING BASED NONCONVEX STOCHASTIC ALGORITHM FOR DECENTRALIZED OPTIMIZATION |
| Songtao Lu; University of Minnesota Twin Cities |
| Xinwei Zhang; University of Minnesota Twin Cities |
| Haoran Sun; University of Minnesota Twin Cities |
| Mingyi Hong; University of Minnesota Twin Cities |
| Paper #2: BYZANTINE-ROBUST STOCHASTIC GRADIENT DESCENT FOR DISTRIBUTED LOW-RANK MATRIX COMPLETION |
| Xuechao He; Sun Yat-Sen University |
| Qing Ling; Sun Yat-Sen University |
| Tianyi Chen; University of Minnesota |
| Paper #3: TRAINING GENERATIVE NETWORKS USING RANDOM DISCRIMINATORS |
| Babak Barazandeh; University of Southern California |
| Meisam Razaviyayn; University of Southern California |
| Maziar Sanjabi; University of Southern California |
| Paper #4: DEEP MIMO DETECTION USING ADMM UNFOLDING |
| Man-Wai Un; Chinese University of Hong Kong |
| Mingjie Shao; Chinese University of Hong Kong |
| Wing-Kin Ma; Chinese University of Hong Kong |
| Pak-Chung Ching; Chinese University of Hong Kong |
| Paper #5: COMPREHENSIVE PERSONALIZED RANKING USING ONE-BIT COMPARISON DATA |
| Aria Ameri; University of Illinois at Chicago |
| Arindam Bose; University of Illinois at Chicago |
| Mojtaba Soltanalian; University of Illinois at Chicago |