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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

Data Amplification: A Unified and Competitive Approach to Property Estimation NIPS 2018
Statistical and Computational Trade-Offs in Kernel K-Means NIPS 2018
Noise2Noise: Learning Image Restoration without Clean Data ICML 2018
On how complexity affects the stability of a predictor AISTATS 2018
Optimal Errors and Phase Transitions in High-Dimensional Generalized Linear Models COLT 2018
Concentration inequalities for empirical processes of linear time series JMLR 2018
Efficient First-Order Algorithms for Adaptive Signal Denoising ICML 2018
Theoretical Analysis of Cross-Validation for Estimating the Risk of the $k$-Nearest Neighbor Classifier JMLR 2018
SAFFRON: an Adaptive Algorithm for Online Control of the False Discovery Rate ICML 2018
Importance sampling for unbiased on-demand evaluation of knowledge base population EMNLP 2017
Cross-lingual and cross-domain discourse segmentation of entire documents ACL 2017
Uniform Convergence Rates for Kernel Density Estimation ICML 2017
On Separability of Loss Functions, and Revisiting Discriminative Vs Generative Models NIPS 2017
Robust Conditional Probabilities NIPS 2017
Rational Distortions of Learners’ Linguistic Input CONLL 2017
Minimax Estimation of Kernel Mean Embeddings JMLR 2017
Early stopping for kernel boosting algorithms: A general analysis with localized complexities NIPS 2017
Sample and Computationally Efficient Learning Algorithms under S-Concave Distributions NIPS 2017
Uniform Deviation Bounds for k-Means Clustering ICML 2017
Fast rates with high probability in exp-concave statistical learning AISTATS 2017
A Universal Analysis of Large-Scale Regularized Least Squares Solutions NIPS 2017
Achieving Optimal Misclassification Proportion in Stochastic Block Models JMLR 2017
On Graph Reconstruction via Empirical Risk Minimization: Fast Learning Rates and Scalability NIPS 2016
Group MAD Competition - A New Methodology to Compare Objective Image Quality Models CVPR 2016
Learning Theory for Distribution Regression JMLR 2016