AML-P.1: Adversarial Machine Learning II |
| Symposium: Signal Processing for Adversarial Machine Learning |
| Session Type: Poster |
| Time: Thursday, November 29, 15:50 - 17:20 |
| Location: Sleeping Beauty Pavilion |
| Session Chairs: Sijia Liu, IBM and Pin-Yu Chen, IBM Research AI |
| Poster Board: 1 |
| AML-P.1.1: MULTI-VIEW FRAME RECONSTRUCTION WITH CONDITIONAL GAN |
| Tahmida Mahmud; University of California, Riverside |
| Mohammad Billah; University of California, Riverside |
| Amit Roy-Chowdhury; University of California, Riverside |
| Poster Board: 2 |
| AML-P.1.2: REINFORCED ADVERSARIAL ATTACKS ON DEEP NEURAL NETWORKS USING ADMM |
| Pu Zhao; Northeastern University |
| Kaidi Xu; Northeastern University |
| Tianyun Zhang; Syracuse University |
| Makan Fardad; Syracuse University |
| Yanzhi Wang; Northeastern University |
| Xue Lin; Northeastern University |
| Poster Board: 3 |
| AML-P.1.3: IS ORDERED WEIGHTED L1 REGULARIZED REGRESSION ROBUST TO ADVERSARIAL PERTURBATION? A CASE STUDY ON OSCAR |
| Pin-Yu Chen; IBM Research AI |
| Bhanukiran Vinzamuri; IBM Research AI |
| Sijia Liu; IBM Research AI |
| Poster Board: 4 |
| AML-P.1.4: ZEROTH-ORDER STOCHASTIC PROJECTED GRADIENT DESCENT FOR NONCONVEX OPTIMIZATION |
| Sijia Liu; IBM Research |
| Xingguo Li; University of Minnesota |
| Pin-Yu Chen; IBM Research |
| Jarvis Haupt; University of Minnesota |
| Lisa Amini; IBM Research |
| Poster Board: 5 |
| AML-P.1.5: ON THE TRADEOFF BETWEEN MODE COLLAPSE AND SAMPLE QUALITY IN GENERATIVE ADVERSARIAL NETWORKS |
| Sudarshan Adiga; University of Arizona |
| Mohamed Adel Attia; University of Arizona |
| Wei-Ting Chang; University of Arizona |
| Ravi Tandon; University of Arizona |
| Poster Board: 6 |
| AML-P.1.6: RANDOM ENSEMBLE OF LOCALLY OPTIMUM DETECTORS FOR DETECTION OF ADVERSARIAL EXAMPLES |
| Amish Goel; University of Illinois at Urbana–Champaign |
| Pierre Moulin; University of Illinois at Urbana–Champaign |
