Papers
Near-Optimal Reinforcement Learning in Dynamic Treatment Regimes
Junzhe Zhang, Elias Bareinboim
Chasing Ghosts: Instruction Following as Bayesian State Tracking
Peter Anderson, Ayush Shrivastava, Devi Parikh et al.
Hierarchical Reinforcement Learning with Advantage-Based Auxiliary Rewards
Siyuan Li, Rui Wang, Minxue Tang et al.
Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates
Carlos Riquelme, Hugo Penedones, Damien Vincent et al.
On the Hardness of Robust Classification
Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska et al.
You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle
Dinghuai Zhang, Tianyuan Zhang, Yiping Lu et al.
Coresets for Clustering with Fairness Constraints
Lingxiao Huang, Shaofeng Jiang, Nisheeth Vishnoi
Communication-Efficient Distributed Blockwise Momentum SGD with Error-Feedback
Shuai Zheng, Ziyue Huang, James Kwok
Optimal Analysis of Subset-Selection Based L_p Low-Rank Approximation
Chen Dan, Hong Wang, Hongyang Zhang et al.
The Implicit Metropolis-Hastings Algorithm
Kirill Neklyudov, Evgenii Egorov, Dmitry P Vetrov
Learnable Tree Filter for Structure-preserving Feature Transform
Lin Song, Yanwei Li, Zeming Li et al.
Full-Gradient Representation for Neural Network Visualization
Suraj Srinivas, François Fleuret
Statistical Analysis of Nearest Neighbor Methods for Anomaly Detection
Xiaoyi Gu, Leman Akoglu, Alessandro Rinaldo
Unsupervised Keypoint Learning for Guiding Class-Conditional Video Prediction
Yunji Kim, Seonghyeon Nam, In Cho et al.
Unified Sample-Optimal Property Estimation in Near-Linear Time
Yi Hao, Alon Orlitsky
Maximum Entropy Monte-Carlo Planning
Chenjun Xiao, Ruitong Huang, Jincheng Mei et al.
Fooling Neural Network Interpretations via Adversarial Model Manipulation
Juyeon Heo, Sunghwan Joo, Taesup Moon
Infra-slow brain dynamics as a marker for cognitive function and decline
Shagun Ajmera, Shreya Rajagopal, Razi Rehman et al.
List-decodable Linear Regression
Sushrut Karmalkar, Adam Klivans, Pravesh Kothari
Coresets for Archetypal Analysis
Sebastian Mair, Ulf Brefeld
Characterizing Bias in Classifiers using Generative Models
Daniel McDuff, Shuang Ma, Yale Song et al.
Approximate Feature Collisions in Neural Nets
Ke Li, Tianhao Zhang, Jitendra Malik
Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks
Gaël Letarte, Pascal Germain, Benjamin Guedj et al.
Efficient Symmetric Norm Regression via Linear Sketching
Zhao Song, Ruosong Wang, Lin Yang et al.
Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods
Kevin Liang, Guoyin Wang, Yitong Li et al.