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
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MLSP-21: Generative Neural Networks

Session Type: Poster
Time: Wednesday, 9 June, 15:30 - 16:15
Location: Gather.Town
Session Chair: Danilo Comminiello, Sapienza University of Rome
 
   MLSP-21.1: DAG-GAN: CAUSAL STRUCTURE LEARNING WITH GENERATIVE ADVERSARIAL NETS
         Yinghua Gao; Tsinghua University
         Li Shen; Tencent AI Lab
         Shu-Tao Xia; Tsinghua University
 
   MLSP-21.2: RELAXED WASSERSTEIN WITH APPLICATIONS TO GANS
         Xin Guo; University of California, Berkeley
         Johnny Hong; University of California, Berkeley
         Tianyi Lin; University of California, Berkeley
         Nan Yang; University of California, Berkeley
 
   MLSP-21.3: ENVIRONMENT-INDEPENDENT WI-FI HUMAN ACTIVITY RECOGNITION WITH ADVERSARIAL NETWORK
         Zhengyang Wang; University of Science and Technology of China
         Sheng Chen; University of Science and Technology of China
         Wei Yang; University of Science and Technology of China
         Yang Xu; University of Science and Technology of China
 
   MLSP-21.4: A ROBUST TO NOISE ADVERSARIAL RECURRENT MODEL FOR NON-INTRUSIVE LOAD MONITORING
         Maria Kaselimi; National Technical University of Athens
         Athanasios Voulodimos; University of West Attica
         Nikolaos Doulamis; National Technical University of Athens
         Anastasios Doulamis; National Technical University of Athens
         Eftychios Protopapadakis; National Technical University of Athens
 
   MLSP-21.5: ENHANCING DATA-FREE ADVERSARIAL DISTILLATION WITH ACTIVATION REGULARIZATION AND VIRTUAL INTERPOLATION
         Xiaoyang Qu; Ping An Technology (Shenzhen) Co., Ltd.
         Jianzong Wang; Ping An Technology (Shenzhen) Co., Ltd.
         Jing Xiao; Ping An Technology (Shenzhen) Co., Ltd.
 
   MLSP-21.6: SEQUENTIAL ADVERSARIAL ANOMALY DETECTION WITH DEEP FOURIER KERNEL
         Shixiang Zhu; Georgia Institute of Technology
         Henry Yuchi; Georgia Institute of Technology
         Minghe Zhang; Georgia Institute of Technology
         Yao Xie; Georgia Institute of Technology