Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..

Journal of Machine Learning Research (JMLR) - 2015

Documentation Rate of Empirical Papers by Reproducibility Variable

Distribution of Empirical Papers by Number of Documented Variables

Website:

Venue Year Papers
Reproducibility Score Reproducibility Score based on Gundersen et al. (2025). See Methods for details.
Documentation Score Documentation Score is the average score over the seven reproducibility variables for empirical research papers. See Methods for details.
% Empirical Percentage of papers that are empirical research vs theoretical research.
% Industry Percentage of empirical research papers with at least one author from Industry.
Website
JMLR 2015 118 0.39 3.65 69.49% 18.29%
Pseudocode
Open Source Code
Open Datasets
Dataset Splits
Hardware Specification
Software Dependencies
Experiment Setup
A Classification Module for Genetic Programming Algorithms in JCLEC 5
A Comprehensive Survey on Safe Reinforcement Learning 0
A Compression Technique for Analyzing Disagreement-Based Active Learning 1
A Direct Estimation of High Dimensional Stationary Vector Autoregressions 4
A Finite Sample Analysis of the Naive Bayes Classifier 1
A General Framework for Fast Stagewise Algorithms 4
A Statistical Perspective on Algorithmic Leveraging 5
A View of Margin Losses as Regularizers of Probability Estimates 4
AD3: Alternating Directions Dual Decomposition for MAP Inference in Graphical Models 6
Absent Data Generating Classifier for Imbalanced Class Sizes 5
Achievability of Asymptotic Minimax Regret by Horizon-Dependent and Horizon-Independent Strategies 1
Adaptive Strategy for Stratified Monte Carlo Sampling 1
Agnostic Insurability of Model Classes 0
Agnostic Learning of Disjunctions on Symmetric Distributions 0
Alexey Chervonenkis's Bibliography 0
Alexey Chervonenkis's Bibliography: Introductory Comments 0
An Asynchronous Parallel Stochastic Coordinate Descent Algorithm 4
Approximate Modified Policy Iteration and its Application to the Game of Tetris 2
Batch Learning from Logged Bandit Feedback through Counterfactual Risk Minimization 5
Bayesian Nonparametric Covariance Regression 6
Bayesian Nonparametric Crowdsourcing 2
CEKA: A Tool for Mining the Wisdom of Crowds 3
Calibrated Multivariate Regression with Application to Neural Semantic Basis Discovery 5
Combination of Feature Engineering and Ranking Models for Paper-Author Identification in KDD Cup 2013 4
Combined l1 and Greedy l0 Penalized Least Squares for Linear Model Selection 3
Comparing Hard and Overlapping Clusterings 5
Completing Any Low-rank Matrix, Provably 2
Complexity of Equivalence and Learning for Multiplicity Tree Automata 1
Composite Self-Concordant Minimization 6
Concave Penalized Estimation of Sparse Gaussian Bayesian Networks 6
Condition for Perfect Dimensionality Recovery by Variational Bayesian PCA 1
Constraint-based Causal Discovery from Multiple Interventions over Overlapping Variable Sets 4
Convergence Rates for Persistence Diagram Estimation in Topological Data Analysis 2
Counting and Exploring Sizes of Markov Equivalence Classes of Directed Acyclic Graphs 4
Decision Boundary for Discrete Bayesian Network Classifiers 0
Derivative Estimation Based on Difference Sequence via Locally Weighted Least Squares Regression 2
Discrete Reproducing Kernel Hilbert Spaces: Sampling and Distribution of Dirac-masses 0
Discrete Restricted Boltzmann Machines 0
Distributed Matrix Completion and Robust Factorization 6
Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates 5
Eigenwords: Spectral Word Embeddings 5
Encog: Library of Interchangeable Machine Learning Models for Java and C# 3
Evolving GPU Machine Code 6
Exceptional Rotations of Random Graphs: A VC Theory 0
Existence and Uniqueness of Proper Scoring Rules 0
Fast Cross-Validation via Sequential Testing 5
Fast Rates in Statistical and Online Learning 0
Flexible High-Dimensional Classification Machines and Their Asymptotic Properties 5
From Dependency to Causality: A Machine Learning Approach 6
Generalized Hierarchical Kernel Learning 5
Geometric Intuition and Algorithms for Ev--SVM 5
Geometry and Expressive Power of Conditional Restricted Boltzmann Machines 1
Global Convergence of Online Limited Memory BFGS 4
Graphical Models via Univariate Exponential Family Distributions 2
Introducing CURRENNT: The Munich Open-Source CUDA RecurREnt Neural Network Toolkit 3
Iterative and Active Graph Clustering Using Trace Norm Minimization Without Cluster Size Constraints 2
Joint Estimation of Multiple Precision Matrices with Common Structures 4
Lasso Screening Rules via Dual Polytope Projection 5
Learning Equilibria of Games via Payoff Queries 1
Learning Sparse Low-Threshold Linear Classifiers 1
Learning Theory of Randomized Kaczmarz Algorithm 1
Learning Transformations for Clustering and Classification 4
Learning Using Privileged Information: Similarity Control and Knowledge Transfer 0
Learning the Structure and Parameters of Large-Population Graphical Games from Behavioral Data 4
Learning to Identify Concise Regular Expressions that Describe Email Campaigns 4
Learning with the Maximum Correntropy Criterion Induced Losses for Regression 3
Linear Dimensionality Reduction: Survey, Insights, and Generalizations 3
Links Between Multiplicity Automata, Observable Operator Models and Predictive State Representations -- a Unified Learning Framework 1
Local Identification of Overcomplete Dictionaries 2
Marginalizing Stacked Linear Denoising Autoencoders 5
Matrix Completion and Low-Rank SVD via Fast Alternating Least Squares 6
Minimax Analysis of Active Learning 1
Multi-layered Gesture Recognition with Kinect 7
Multiclass Learnability and the ERM Principle 1
Multimodal Gesture Recognition via Multiple Hypotheses Rescoring 5
Network Granger Causality with Inherent Grouping Structure 3
Non-Asymptotic Analysis of a New Bandit Algorithm for Semi-Bounded Rewards 3
On Linearly Constrained Minimum Variance Beamforming 3
On Semi-Supervised Linear Regression in Covariate Shift Problems 5
On the Asymptotic Normality of an Estimate of a Regression Functional 0
On the Inductive Bias of Dropout 0
Online Learning via Sequential Complexities 1
Online Tensor Methods for Learning Latent Variable Models 6
Optimal Bayesian Estimation in Random Covariate Design with a Rescaled Gaussian Process Prior 0
Optimal Estimation of Low Rank Density Matrices 0
Optimality of Poisson Processes Intensity Learning with Gaussian Processes 0
PAC Optimal MDP Planning with Application to Invasive Species Management 2
Perturbed Message Passing for Constraint Satisfaction Problems 3
Photonic Delay Systems as Machine Learning Implementations 3
Plug-and-Play Dual-Tree Algorithm Runtime Analysis 2
Predicting a Switching Sequence of Graph Labelings 1
Preface to this Special Issue 0
RLPy: A Value-Function-Based Reinforcement Learning Framework for Education and Research 2
Rationality, Optimism and Guarantees in General Reinforcement Learning 1
Regularized M-estimators with Nonconvexity: Statistical and Algorithmic Theory for Local Optima 1
Response-Based Approachability with Applications to Generalized No-Regret Problems 1
Risk Bounds for the Majority Vote: From a PAC-Bayesian Analysis to a Learning Algorithm 5
SAMOA: Scalable Advanced Massive Online Analysis 4
Second-Order Non-Stationary Online Learning for Regression 3
Semi-Supervised Interpolation in an Anticausal Learning Scenario 0
Sharp Oracle Bounds for Monotone and Convex Regression Through Aggregation 0
Simultaneous Pursuit of Sparseness and Rank Structures for Matrix Decomposition 4
SnFFT: A Julia Toolkit for Fourier Analysis of Functions over Permutations 1
Statistical Decision Making for Optimal Budget Allocation in Crowd Labeling 3
Statistical Topological Data Analysis using Persistence Landscapes 1
Strong Consistency of the Prototype Based Clustering in Probabilistic Space 0
Supervised Learning via Euler's Elastica Models 4
The Algebraic Combinatorial Approach for Low-Rank Matrix Completion 3
The Libra Toolkit for Probabilistic Models 1
The Randomized Causation Coefficient 5
The Sample Complexity of Learning Linear Predictors with the Squared Loss 0
The flare Package for High Dimensional Linear Regression and Precision Matrix Estimation in R 3
Towards an Axiomatic Approach to Hierarchical Clustering of Measures 0
Ultra-Scalable and Efficient Methods for Hybrid Observational and Experimental Local Causal Pathway Discovery 6
V-Matrix Method of Solving Statistical Inference Problems 3
When Are Overcomplete Topic Models Identifiable? Uniqueness of Tensor Tucker Decompositions with Structured Sparsity 0
partykit: A Modular Toolkit for Recursive Partytioning in R 2
pyGPs -- A Python Library for Gaussian Process Regression and Classification 2