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TU2.I: Adversarial Machine Learning

Session Type: Lecture
Time: Tuesday, 5 May, 16:30 - 18:30
Location: On-Demand
Session Chair: Zheng-Hua Tan, Aalborg University
 
   TU2.I.1: HEADLESS HORSEMAN: ADVERSARIAL ATTACKS ON TRANSFER LEARNING MODELS
         Ahmed Abdelkader; University of Maryland
         Michael Curry; University of Maryland
         Liam Fowl; University of Maryland
         Tom Goldstein; University of Maryland
         Avi Schwarzschild; University of Maryland
         Manli Shu; University of Maryland
         Christoph Studer; Cornell Tech
         Chen Zhu; University of Maryland
 
   TU2.I.2: DETECTING ADVERSARIAL ATTACKS IN TIME-SERIES DATA
         Mubarak Abdu-Aguye; Egypt-Japan University of Science and Technology
         Walid Gomaa; Egypt-Japan University of Science and Technology
         Yasushi Makihara; Osaka University
         Yasushi Yagi; Osaka University
 
   TU2.I.3: DETECTION OF ADVERSARIAL ATTACKS AND CHARACTERIZATION OF ADVERSARIAL SUBSPACE
         Mohammad Esmaeilpour; École de Technologie Supérieure
         Patrick Cardinal; École de Technologie Supérieure
         Alessandro Lameiras Koerich; École de Technologie Supérieure
 
   TU2.I.4: ADVERSARIAL EXAMPLE DETECTION BY CLASSIFICATION FOR DEEP SPEECH RECOGNITION
         Saeid Samizade; Aalborg University
         Zheng-Hua Tan; Aalborg University
         Chao Shen; Xi'an Jiaotong University
         Xiaohong Guan; Xi'an Jiaotong University
 
   TU2.I.5: CHARACTERIZING SPEECH ADVERSARIAL EXAMPLES USING SELF-ATTENTION U-NET ENHANCEMENT
         Chao-Han Huck Yang; Georgia Institute of Technology
         Jun Qi; Georgia Institute of Technology
         Pin-Yu Chen; IBM Research
         Xiaoli Ma; Georgia Institute of Technology
         Chin-Hui Lee; Georgia Institute of Technology
 
   TU2.I.6: ACTION-MANIPULATION ATTACKS ON STOCHASTIC BANDITS
         Guanlin Liu; University of California, Davis
         Lifeng Lai; University of California, Davis