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Statistical Learning

4,117 papers

Papers per year

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100
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Papers

Streaming Kernel PCA with $\tilde{O}(\sqrt{n})$ Random Features NIPS 2018
Differentially Private Testing of Identity and Closeness of Discrete Distributions NIPS 2018
The Sample Complexity of Semi-Supervised Learning with Nonparametric Mixture Models NIPS 2018
Estimating Learnability in the Sublinear Data Regime NIPS 2018
Chaining Mutual Information and Tightening Generalization Bounds NIPS 2018
PAC-learning in the presence of adversaries NIPS 2018
Entropy Rate Estimation for Markov Chains with Large State Space NIPS 2018
Data-dependent PAC-Bayes priors via differential privacy NIPS 2018
Robust Hypothesis Testing Using Wasserstein Uncertainty Sets NIPS 2018
Mallows Models for Top-k Lists NIPS 2018
Data Amplification: A Unified and Competitive Approach to Property Estimation NIPS 2018
Testing for Families of Distributions via the Fourier Transform NIPS 2018
Model-Agnostic Private Learning NIPS 2018
On the Dimensionality of Word Embedding NIPS 2018
Learning without the Phase: Regularized PhaseMax Achieves Optimal Sample Complexity NIPS 2018
Near-Optimal Time and Sample Complexities for Solving Markov Decision Processes with a Generative Model NIPS 2018
On Learning Markov Chains NIPS 2018
Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds NIPS 2018
Practical Methods for Graph Two-Sample Testing NIPS 2018
Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate NIPS 2018
Minimax Statistical Learning with Wasserstein distances NIPS 2018
Tight Bounds for Collaborative PAC Learning via Multiplicative Weights NIPS 2018
Differentially Private Change-Point Detection NIPS 2018
Manifold Structured Prediction NIPS 2018
Assessing Generative Models via Precision and Recall NIPS 2018