Papers
A Discrete Variational Recurrent Topic Model without the Reparametrization Trick
Mehdi Rezaee, Francis Ferraro
Advances in Black-Box VI: Normalizing Flows, Importance Weighting, and Optimization
Abhinav Agrawal, Daniel R. Sheldon, Justin Domke
Adversarial Attacks on Deep Graph Matching
Zijie Zhang, Zeru Zhang, Yang Zhou et al.
Adversarial Attacks on Linear Contextual Bandits
Evrard Garcelon, Baptiste Roziere, Laurent Meunier et al.
Adversarial Bandits with Corruptions: Regret Lower Bound and No-regret Algorithm
lin yang, Mohammad Hajiesmaili, Mohammad Sadegh Talebi et al.
Adversarial Blocking Bandits
Nicholas Bishop, Hau Chan, Debmalya Mandal et al.
Adversarial Counterfactual Learning and Evaluation for Recommender System
Da Xu, Chuanwei Ruan, Evren Korpeoglu et al.
Adversarial Crowdsourcing Through Robust Rank-One Matrix Completion
Qianqian Ma, Alex Olshevsky
Adversarial Distributional Training for Robust Deep Learning
Yinpeng Dong, Zhijie Deng, Tianyu Pang et al.
Adversarial Example Games
Joey Bose, Gauthier Gidel, Hugo Berard et al.
Adversarial Learning for Robust Deep Clustering
Xu Yang, Cheng Deng, Kun Wei et al.
Adversarially-learned Inference via an Ensemble of Discrete Undirected Graphical Models
Adarsh Keshav Jeewajee, Leslie P. Kaelbling
Adversarially Robust Few-Shot Learning: A Meta-Learning Approach
Micah Goldblum, Liam Fowl, Tom Goldstein
Adversarially Robust Streaming Algorithms via Differential Privacy
Avinatan Hasidim, Haim Kaplan, Yishay Mansour et al.
Adversarial Robustness of Supervised Sparse Coding
Jeremias Sulam, Ramchandran Muthukumar, Raman Arora
Adversarial robustness via robust low rank representations
Pranjal Awasthi, Himanshu Jain, Ankit Singh Rawat et al.
Adversarial Self-Supervised Contrastive Learning
Minseon Kim, Jihoon Tack, Sung Ju Hwang
Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization
Paul Barde, Julien Roy, Wonseok Jeon et al.
Adversarial Sparse Transformer for Time Series Forecasting
Sifan Wu, Xi Xiao, Qianggang Ding et al.
Adversarial Style Mining for One-Shot Unsupervised Domain Adaptation
Yawei Luo, Ping Liu, Tao Guan et al.
Adversarial Training is a Form of Data-dependent Operator Norm Regularization
Kevin Roth, Yannic Kilcher, Thomas Hofmann
Adversarial Weight Perturbation Helps Robust Generalization
Dongxian Wu, Shu-Tao Xia, Yisen Wang
AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing Flows
Hadi Mohaghegh Dolatabadi, Sarah Erfani, Christopher Leckie
A Dynamical Central Limit Theorem for Shallow Neural Networks
Zhengdao Chen, Grant Rotskoff, Joan Bruna et al.
A Fair Classifier Using Kernel Density Estimation
Jaewoong Cho, Gyeongjo Hwang, Changho Suh