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Methodology
← Optimization & Theory
Machine Learning
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Optimization & Theory
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Statistics
684 directly classified papers
Papers per year
2004: 1
2005: 1
2006: 3
2007: 10
2008: 6
2009: 9
2010: 11
2011: 16
2012: 31
2013: 31
2014: 23
2015: 12
2016: 18
2017: 29
2018: 39
2019: 29
2020: 46
2021: 64
2022: 88
2023: 73
2024: 105
2025: 39
Papers
A Kernelised Stein Statistic for Assessing Implicit Generative Models
NIPS 2022
Split-kl and PAC-Bayes-split-kl Inequalities for Ternary Random Variables
NIPS 2022
Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions
NIPS 2022
Falsification before Extrapolation in Causal Effect Estimation
NIPS 2022
Learning with little mixing
NIPS 2022
On the Efficient Implementation of High Accuracy Optimality of Profile Maximum Likelihood
NIPS 2022
Intrinsic dimensionality estimation using Normalizing Flows
NIPS 2022
Inferring Cause and Effect in the Presence of Heteroscedastic Noise
ICML 2022
Inter-annotator agreement is not the ceiling of machine learning performance: Evidence from a comprehensive set of simulations
ACL 2022
Convergence Rates for Gaussian Mixtures of Experts
JMLR 2022
Exact Paired-Permutation Testing for Structured Test Statistics
NAACL 2022
Nonparametric Neighborhood Selection in Graphical Models
JMLR 2022
Intrinsic Dimension Estimation Using Wasserstein Distance
JMLR 2022
A Random Matrix Analysis of Data Stream Clustering: Coping With Limited Memory Resources
ICML 2022
Communication-Constrained Distributed Quantile Regression with Optimal Statistical Guarantees
JMLR 2022
A Unified Statistical Learning Model for Rankings and Scores with Application to Grant Panel Review
JMLR 2022
Assessing Digital Language Support on a Global Scale
COLING 2022
Testing Whether a Learning Procedure is Calibrated
JMLR 2022
Three rates of convergence or separation via U-statistics in a dependent framework
JMLR 2022
Statistical inference with implicit SGD: proximal Robbins-Monro vs. Polyak-Ruppert
ICML 2022
Distributed Bootstrap for Simultaneous Inference Under High Dimensionality
JMLR 2022
Estimating Density Models with Truncation Boundaries using Score Matching
JMLR 2022
Learning Rates as a Function of Batch Size: A Random Matrix Theory Approach to Neural Network Training
JMLR 2022
Scalable and Efficient Hypothesis Testing with Random Forests
JMLR 2022
Power Iteration for Tensor PCA
JMLR 2022
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