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Statistical Learning

4,117 papers

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Papers

Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance Sampling ICML 2020
Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative Priors ICML 2020
Learning Deep Kernels for Non-Parametric Two-Sample Tests ICML 2020
Fast and Consistent Learning of Hidden Markov Models by Incorporating Non-Consecutive Correlations ICML 2020
The Role of Regularization in Classification of High-dimensional Noisy Gaussian Mixture ICML 2020
Reliable Fidelity and Diversity Metrics for Generative Models ICML 2020
In Defense of Uniform Convergence: Generalization via Derandomization with an Application to Interpolating Predictors ICML 2020
Aggregation of Multiple Knockoffs ICML 2020
Consistent Structured Prediction with Max-Min Margin Markov Networks ICML 2020
Reducing Sampling Error in Batch Temporal Difference Learning ICML 2020
Performative Prediction ICML 2020
Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field Approximation ICML 2020
Robust One-Bit Recovery via ReLU Generative Networks: Near-Optimal Statistical Rate and Global Landscape Analysis ICML 2020
Optimistic Bounds for Multi-output Learning ICML 2020
On Semi-parametric Inference for BART ICML 2020
From PAC to Instance-Optimal Sample Complexity in the Plackett-Luce Model ICML 2020
Detecting Out-of-Distribution Examples with Gram Matrices ICML 2020
On Conditional Versus Marginal Bias in Multi-Armed Bandits ICML 2020
Robustness to Spurious Correlations via Human Annotations ICML 2020
Doubly robust off-policy evaluation with shrinkage ICML 2020
Adaptive Estimator Selection for Off-Policy Evaluation ICML 2020
Alleviating Privacy Attacks via Causal Learning ICML 2020
From ImageNet to Image Classification: Contextualizing Progress on Benchmarks ICML 2020
Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks Using PAC-Bayesian Analysis ICML 2020
Logistic Regression for Massive Data with Rare Events ICML 2020