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Poster
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Thu 2:30
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PEARL: Data Synthesis via Private Embeddings and Adversarial Reconstruction Learning
Seng Pei Liew · Tsubasa Takahashi · Michihiko Ueno
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Poster
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Tue 18:30
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A Unified Wasserstein Distributional Robustness Framework for Adversarial Training
Anh Bui · Trung Le · Quan Tran · He Zhao · Dinh Phung
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Poster
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Tue 2:30
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Distributionally Robust Models with Parametric Likelihood Ratios
Paul Michel · Tatsunori Hashimoto · Graham Neubig
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Poster
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Thu 10:30
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Demystifying Limited Adversarial Transferability in Automatic Speech Recognition Systems
Hadi Abdullah · Aditya Karlekar · Vincent Bindschaedler · Patrick Traynor
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Workshop
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Learning Category-Level Generalizable Object Manipulation Policy via Generative Adversarial Self-Imitation Learning from Demonstrations
Hao Shen · Weikang Wan · He Wang
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Poster
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Mon 18:30
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Towards Evaluating the Robustness of Neural Networks Learned by Transduction
Jiefeng Chen · Xi Wu · Yang Guo · Yingyu Liang · Somesh Jha
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Poster
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Tue 10:30
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Post-Training Detection of Backdoor Attacks for Two-Class and Multi-Attack Scenarios
Zhen Xiang · David Miller · George Kesidis
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Workshop
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Learning Robust Algorithms for Online Allocation Problems Using Adversarial Training
Goran Zuzic · Di Wang · Aranyak Mehta · D. Sivakumar
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Workshop
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Fri 10:45
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Learning Robust Algorithms for Online Allocation Problems Using Adversarial Training
Goran Zuzic · Di Wang · Aranyak Mehta · D. Sivakumar
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Poster
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Thu 10:30
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Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?
Vikash Sehwag · Saeed Mahloujifar · Tinashe Handina · Sihui Dai · Chong Xiang · Mung Chiang · Prateek Mittal
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Poster
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Thu 10:30
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TPU-GAN: Learning temporal coherence from dynamic point cloud sequences
Zijie Li · Tianqin Li · Amir Barati Farimani
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Poster
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Tue 18:30
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Robust Unlearnable Examples: Protecting Data Privacy Against Adversarial Learning
Shaopeng Fu · Fengxiang He · Yang Liu · Li Shen · Dacheng Tao
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