Statistical Learning

Optimal Multi-Distribution Learning COLT 2024 Optimal Private and Communication Constraint Distributed Goodness-of-Fit Testing for Discrete Distributions in the Large Sample Regime NeurIPS 2024 Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms NeurIPS 2024 Optimal Zero-Shot Detector for Multi-Armed Attacks AISTATS 2024 Order of Magnitude Speedups for LLM Membership Inference EMNLP 2024 PAC-Bayes-Chernoff bounds for unbounded losses NeurIPS 2024 PAC-Bayes Generalisation Bounds for Dynamical Systems including Stable RNNs AAAI 2024 PaCoST: Paired Confidence Significance Testing for Benchmark Contamination Detection in Large Language Models EMNLP 2024 Paloma: A Benchmark for Evaluating Language Model Fit NeurIPS 2024 Perceptual Scales Predicted by Fisher Information Metrics ICLR 2024 Performance Gaps in Multi-view Clustering under the Nested Matrix-Tensor Model ICLR 2024 Permutation-Based Hypothesis Testing for Neural Networks AAAI 2024 Personalized PCA: Decoupling Shared and Unique Features JMLR 2024 Piecewise-Stationary Bandits with Knapsacks NeurIPS 2024 Post-Regularization Confidence Bands for Ordinary Differential Equations JMLR 2024 Precise asymptotics of reweighted least-squares algorithms for linear diagonal networks NeurIPS 2024 Precise Model Benchmarking with Only a Few Observations EMNLP 2024 Predicting Ground State Properties: Constant Sample Complexity and Deep Learning Algorithms NeurIPS 2024 Predicting the Performance of Foundation Models via Agreement-on-the-Line NeurIPS 2024 Prediction from compression for models with infinite memory, with applications to hidden Markov and renewal processes COLT 2024 Prediction-Powered Ranking of Large Language Models NeurIPS 2024 Predictive Inference with Weak Supervision JMLR 2024 Privately Learning Smooth Distributions on the Hypercube by Projections ICML 2024 Private Online Learning via Lazy Algorithms NeurIPS 2024 Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages ICML 2024