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Statistical Learning

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Papers

Spectral Methods for Ranking with Scarce Data UAI 2020
Semi-Supervised Learning: the Case When Unlabeled Data is Equally Useful UAI 2020
Adapting Text Embeddings for Causal Inference UAI 2020
Risk Bounds for Low Cost Bipartite Ranking UAI 2020
Active Model Estimation in Markov Decision Processes UAI 2020
Estimation Rates for Sparse Linear Cyclic Causal Models UAI 2020
EiGLasso: Scalable Estimation of Cartesian Product of Sparse Inverse Covariance Matrices UAI 2020
Order Optimal One-Shot Distributed Learning NIPS 2019
Uniform convergence may be unable to explain generalization in deep learning NIPS 2019
First order expansion of convex regularized estimators NIPS 2019
Localized Structured Prediction NIPS 2019
Minimizers of the Empirical Risk and Risk Monotonicity NIPS 2019
Statistical-Computational Tradeoff in Single Index Models NIPS 2019
Distributionally Robust Optimization and Generalization in Kernel Methods NIPS 2019
Generalization Error Analysis of Quantized Compressive Learning NIPS 2019
Likelihood-Free Overcomplete ICA and Applications In Causal Discovery NIPS 2019
Data-Dependence of Plateau Phenomenon in Learning with Neural Network --- Statistical Mechanical Analysis NIPS 2019
Detecting Overfitting via Adversarial Examples NIPS 2019
The spiked matrix model with generative priors NIPS 2019
Hypothesis Set Stability and Generalization NIPS 2019
Practical and Consistent Estimation of f-Divergences NIPS 2019
PAC-Bayes under potentially heavy tails NIPS 2019
Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments NIPS 2019
PAC-Bayes Un-Expected Bernstein Inequality NIPS 2019
Graph-Based Semi-Supervised Learning with Non-ignorable Non-response NIPS 2019