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statistical learning

350 papers

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learning theory (518) sample complexity (1158) generalization bound (649) convergence rate (606) empirical risk minimization (348) information theory (489) bayesian inference (1904) hypothesis testing (254) differential privacy (1010) statistical learning theory (82)

Papers

Tighter Expected Generalization Error Bounds via Wasserstein Distance NIPS 2021
Differentially Private Sampling from Distributions NIPS 2021
Hilbert Sinkhorn Divergence for Optimal Transport CVPR 2021
Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals NIPS 2021
A Computationally Efficient Method for Learning Exponential Family Distributions NIPS 2021
Stability and Risk Bounds of Iterative Hard Thresholding AISTATS 2021
On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians ALT 2021
Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance MLHC 2021
Fair Comparison: Quantifying Variance in Results for Fine-Grained Visual Categorization WACV 2021
Learning with invariances in random features and kernel models COLT 2021
Risk Monotonicity in Statistical Learning NIPS 2021
The All-or-Nothing Phenomenon in Sparse Tensor PCA NIPS 2020
PAC-Bayes Learning Bounds for Sample-Dependent Priors NIPS 2020
Learning discrete distributions: user vs item-level privacy NIPS 2020
Effectively Unbiased FID and Inception Score and Where to Find Them CVPR 2020
A Flexible Framework for Nonparametric Graphical Modeling that Accommodates Machine Learning ICML 2020
The Optimal Ridge Penalty for Real-world High-dimensional Data Can Be Zero or Negative due to the Implicit Ridge Regularization JMLR 2020
Random Matrix Theory Proves that Deep Learning Representations of GAN-data Behave as Gaussian Mixtures ICML 2020
Hypothesis Testing Interpretations and Renyi Differential Privacy AISTATS 2020
Feature Noise Induces Loss Discrepancy Across Groups ICML 2020
Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing ICML 2020
Sharp Statistical Guaratees for Adversarially Robust Gaussian Classification ICML 2020
Statistical Learning with a Nuisance Component (Extended Abstract) IJCAI 2020
Kernel Alignment Risk Estimator: Risk Prediction from Training Data NIPS 2020
Minimax Estimation of Conditional Moment Models NIPS 2020