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Statistical Learning

4076 directly classified papers

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Papers

Instability, Computational Efficiency and Statistical Accuracy JMLR 2025
Certified Machine Unlearning Under High Dimensional Regime JMLR 2025
Uncertainty in Causality: A New Frontier ACL 2025
Statistical inference on black-box generative models in the data kernel perspective space ACL 2025
Measuring Mental Health Variables in Computational Research: Toward Validated, Dimensional, and Transdiagnostic Approaches NAACL 2025
Don’t Sweat the Small Stuff: Segment-Level Meta-Evaluation Based on Pairwise Difference Correlation EMNLP 2025
DOVE: A Large-Scale Multi-Dimensional Predictions Dataset Towards Meaningful LLM Evaluation ACL 2025
Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation JMLR 2025
Unbalanced Kantorovich-Rubinstein distance, plan, and barycenter on nite spaces: A statistical perspective JMLR 2025
Bayes Meets Bernstein at the Meta Level: an Analysis of Fast Rates in Meta-Learning with PAC-Bayes JMLR 2025
Uplift Model Evaluation with Ordinal Dominance Graphs JMLR 2025
Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress? NIPS 2024
Piecewise-Stationary Bandits with Knapsacks NIPS 2024
Data Distribution Valuation NIPS 2024
Robust Sparse Regression with Non-Isotropic Designs NIPS 2024
BrainBits: How Much of the Brain are Generative Reconstruction Methods Using? NIPS 2024
Cousins Of The Vendi Score: A Family Of Similarity-Based Diversity Metrics For Science And Machine Learning AISTATS 2024
Consistent and Asymptotically Unbiased Estimation of Proper Calibration Errors AISTATS 2024
Near-Interpolators: Rapid Norm Growth and the Trade-Off between Interpolation and Generalization AISTATS 2024
Sample and Computationally Efficient Robust Learning of Gaussian Single-Index Models NIPS 2024
Non-vacuous Generalization Bounds for Adversarial Risk in Stochastic Neural Networks AISTATS 2024
DAGnosis: Localized Identification of Data Inconsistencies using Structures AISTATS 2024
Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics NIPS 2024
Differentially Private Equivalence Testing for Continuous Distributions and Applications NIPS 2024
Improved Regret of Linear Ensemble Sampling NIPS 2024