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Methodology
← Optimization & Theory
Machine Learning
›
Optimization & Theory
›
Statistical Learning
4076 directly classified papers
Papers per year
2001: 2
2002: 8
2003: 9
2004: 7
2005: 9
2006: 34
2007: 37
2008: 34
2009: 41
2010: 62
2011: 68
2012: 81
2013: 109
2014: 120
2015: 99
2016: 149
2017: 160
2018: 205
2019: 285
2020: 376
2021: 433
2022: 447
2023: 577
2024: 488
2025: 192
2026: 44
Papers
Provable Generalization of Overparameterized Meta-learning Trained with SGD
NIPS 2022
Robust Testing in High-Dimensional Sparse Models
NIPS 2022
Normalizing Flows for Knockoff-free Controlled Feature Selection
NIPS 2022
Robust Generalized Method of Moments: A Finite Sample Viewpoint
NIPS 2022
Neural Mean Discrepancy for Efficient Out-of-Distribution Detection
CVPR 2022
Private and Communication-Efficient Algorithms for Entropy Estimation
NIPS 2022
Network change point localisation under local differential privacy
NIPS 2022
Learning the Structure of Large Networked Systems Obeying Conservation Laws
NIPS 2022
A Conditional Randomization Test for Sparse Logistic Regression in High-Dimension
NIPS 2022
Distributed Learning of Conditional Quantiles in the Reproducing Kernel Hilbert Space
NIPS 2022
On Margins and Generalisation for Voting Classifiers
NIPS 2022
Statistical Learning and Inverse Problems: A Stochastic Gradient Approach
NIPS 2022
Learning Mixed Multinomial Logits with Provable Guarantees
NIPS 2022
A Statistical Online Inference Approach in Averaged Stochastic Approximation
NIPS 2022
Anonymized Histograms in Intermediate Privacy Models
NIPS 2022
Outlier-Robust Sparse Estimation via Non-Convex Optimization
NIPS 2022
Privacy Induces Robustness: Information-Computation Gaps and Sparse Mean Estimation
NIPS 2022
On the Efficient Implementation of High Accuracy Optimality of Profile Maximum Likelihood
NIPS 2022
Subspace Recovery from Heterogeneous Data with Non-isotropic Noise
NIPS 2022
A PAC-Bayesian Generalization Bound for Equivariant Networks
NIPS 2022
Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions
NIPS 2022
Precise Learning Curves and Higher-Order Scalings for Dot-product Kernel Regression
NIPS 2022
Optimal Rates for Regularized Conditional Mean Embedding Learning
NIPS 2022
A General Framework for Auditing Differentially Private Machine Learning
NIPS 2022
Debiased Machine Learning without Sample-Splitting for Stable Estimators
NIPS 2022
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