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← Optimization & Theory
Machine Learning
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Optimization & Theory
›
Statistical Learning
4,076 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
Statistical Query Lower Bounds for Tensor PCA
JMLR 2021
Variance Reduced Median-of-Means Estimator for Byzantine-Robust Distributed Inference
JMLR 2021
Consistent Semi-Supervised Graph Regularization for High Dimensional Data
JMLR 2021
Adaptive estimation of nonparametric functionals
JMLR 2021
Learning a High-dimensional Linear Structural Equation Model via l1-Regularized Regression
JMLR 2021
Online stochastic gradient descent on non-convex losses from high-dimensional inference
JMLR 2021
Towards a Unified Analysis of Random Fourier Features
JMLR 2021
Non-parametric Quantile Regression via the K-NN Fused Lasso
JMLR 2021
An Importance Weighted Feature Selection Stability Measure
JMLR 2021
Integrative High Dimensional Multiple Testing with Heterogeneity under Data Sharing Constraints
JMLR 2021
Optimal Bounds between f-Divergences and Integral Probability Metrics
JMLR 2021
Finite-sample Analysis of Interpolating Linear Classifiers in the Overparameterized Regime
JMLR 2021
Learning Whenever Learning is Possible: Universal Learning under General Stochastic Processes
JMLR 2021
Locally Differentially-Private Randomized Response for Discrete Distribution Learning
JMLR 2021
Nonparametric Modeling of Higher-Order Interactions via Hypergraphons
JMLR 2021
Universal consistency and rates of convergence of multiclass prototype algorithms in metric spaces
JMLR 2021
Kernel Smoothing, Mean Shift, and Their Learning Theory with Directional Data
JMLR 2021
What Causes the Test Error? Going Beyond Bias-Variance via ANOVA
JMLR 2021
Information criteria for non-normalized models
JMLR 2021
PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review
JMLR 2021
Improving Reproducibility in Machine Learning Research(A Report from the NeurIPS 2019 Reproducibility Program)
JMLR 2021
Asymptotic Normality, Concentration, and Coverage of Generalized Posteriors
JMLR 2021
Unlinked Monotone Regression
JMLR 2021
Prediction Under Latent Factor Regression: Adaptive PCR, Interpolating Predictors and Beyond
JMLR 2021
On the Estimation of Network Complexity: Dimension of Graphons
JMLR 2021
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