Papers
Revisiting the Bethe-Hessian: Improved Community Detection in Sparse Heterogeneous Graphs
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay
PAC-Bayes Un-Expected Bernstein Inequality
Zakaria Mhammedi, Peter Grünwald, Benjamin Guedj
Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints
Sebastian Tschiatschek, Ahana Ghosh, Luis Haug et al.
Provably Efficient Q-learning with Function Approximation via Distribution Shift Error Checking Oracle
Simon S Du, Yuping Luo, Ruosong Wang et al.
More Is Less: Learning Efficient Video Representations by Big-Little Network and Depthwise Temporal Aggregation
Quanfu Fan, Chun-Fu (Richard) Chen, Hilde Kuehne et al.
A Geometric Perspective on Optimal Representations for Reinforcement Learning
Marc Bellemare, Will Dabney, Robert Dadashi et al.
Stability of Graph Scattering Transforms
Fernando Gama, Alejandro Ribeiro, Joan Bruna
Optimizing Generalized Rate Metrics with Three Players
Harikrishna Narasimhan, Andrew Cotter, Maya Gupta
On Fenchel Mini-Max Learning
Chenyang Tao, Liqun Chen, Shuyang Dai et al.
Differentially Private Distributed Data Summarization under Covariate Shift
Kanthi Sarpatwar, Karthikeyan Shanmugam, Venkata Sitaramagiridharganesh Ganapavarapu et al.
Interaction Hard Thresholding: Consistent Sparse Quadratic Regression in Sub-quadratic Time and Space
Shuo Yang, Yanyao Shen, Sujay Sanghavi
A Structured Prediction Approach for Generalization in Cooperative Multi-Agent Reinforcement Learning
Nicolas Carion, Nicolas Usunier, Gabriel Synnaeve et al.
Complexity of Highly Parallel Non-Smooth Convex Optimization
Sebastien Bubeck, Qijia Jiang, Yin-Tat Lee et al.
Private Stochastic Convex Optimization with Optimal Rates
Raef Bassily, Vitaly Feldman, Kunal Talwar et al.
Principal Component Projection and Regression in Nearly Linear Time through Asymmetric SVRG
Yujia Jin, Aaron Sidford
Mapping State Space using Landmarks for Universal Goal Reaching
Zhiao Huang, Fangchen Liu, Hao Su
Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments
Vasilis Syrgkanis, Victor Lei, Miruna Oprescu et al.
Compacting, Picking and Growing for Unforgetting Continual Learning
Ching-Yi Hung, Cheng-Hao Tu, Cheng-En Wu et al.
CXPlain: Causal Explanations for Model Interpretation under Uncertainty
Patrick Schwab, Walter Karlen
Efficient Neural Architecture Transformation Search in Channel-Level for Object Detection
Junran Peng, Ming Sun, ZHAO-XIANG ZHANG et al.
Regression Planning Networks
Danfei Xu, Roberto Martín-Martín, De-An Huang et al.
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers
Hadi Salman, Jerry Li, Ilya Razenshteyn et al.
PAC-Bayes under potentially heavy tails
Matthew Holland
Handling correlated and repeated measurements with the smoothed multivariate square-root Lasso
Quentin Bertrand, Mathurin Massias, Alexandre Gramfort et al.