2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

Technical Program

MLSP-39: Adversarial Machine Learning

Session Type: Poster
Time: Friday, 11 June, 11:30 - 12:15
Location: Gather.Town
Session Chair: George Atia, University of Central Florida
 
MLSP-39.1: ADVERSARIAL LEARNING VIA PROBABILISTIC PROXIMITY ANALYSIS
         Jarrod Hollis; Oregon State University
         Jinsub Kim; Oregon State University
         Raviv Raich; Oregon State University
 
MLSP-39.2: CLASS AWARE ROBUST TRAINING
         Zhikang Xia; Tsinghua Shenzhen International Graduate School, Tsinghua University
         Bin Chen; Tsinghua Shenzhen International Graduate School, Tsinghua University
         Tao Dai; Tsinghua Shenzhen International Graduate School, Tsinghua University
         Shutao Xia; Tsinghua Shenzhen International Graduate School, Tsinghua University
 
MLSP-39.3: NON-SINGULAR ADVERSARIAL ROBUSTNESS OF NEURAL NETWORKS
         Yu-Lin Tsai; National Chiao Tung University
         Chia-Yi Hsu; National Chiao Tung University
         Chia-Mu Yu; National Chiao Tung University
         Pin-Yu Chen; IBM Research
 
MLSP-39.4: TOWARDS ADVERSARIAL ROBUSTNESS VIA COMPACT FEATURE REPRESENTATIONS
         Muhammad Shah; Carnegie Mellon University
         Raphael Olivier; Carnegie Mellon University
         Bhiksha Raj; Carnegie Mellon University
 
MLSP-39.5: ADVERSARIAL EXAMPLES DETECTION BEYOND IMAGE SPACE
         Kejiang Chen; University of Science and Technology of China
         Yuefeng Chen; Alibaba group
         Hang Zhou; University of Science and Technology of China
         Chuan Qin; University of Science and Technology of China
         Xiaofeng Mao; Alibaba group
         Weiming Zhang; University of Science and Technology of China
         NengHai Yu; University of Science and Technology of China
 
MLSP-39.6: STRONG DATA AUGMENTATION SANITIZES POISONING AND BACKDOOR ATTACKS WITHOUT AN ACCURACY TRADEOFF
         Eitan Borgnia; University of Maryland, College Park
         Valeriia Cherepanova; University of Maryland, College Park
         Liam Fowl; University of Maryland, College Park
         Amin Ghiasi; University of Maryland, College Park
         Jonas Geiping; University of Siegen
         Micah Goldblum; University of Maryland, College Park
         Tom Goldstein; University of Maryland, College Park
         Arjun Gupta; University of Maryland, College Park