Statistical Learning

Minimax Excess Risk of First-Order Methods for Statistical Learning with Data-Dependent Oracles AISTATS 2024 Minimax Linear Regression under the Quantile Risk COLT 2024 Minimax optimal density estimation using a shallow generative model with a one-dimensional latent variable AISTATS 2024 Minimax Optimality of Score-based Diffusion Models: Beyond the Density Lower Bound Assumptions ICML 2024 Minimax Rates for High-Dimensional Random Tessellation Forests JMLR 2024 Minimum Entropy Coupling with Bottleneck NeurIPS 2024 Mission Impossible: A Statistical Perspective on Jailbreaking LLMs NeurIPS 2024 Mitigating Frequency Bias and Anisotropy in Language Model Pre-Training with Syntactic Smoothing EMNLP 2024 MMD-based Variable Importance for Distributional Random Forest AISTATS 2024 Model Collapse Demystified: The Case of Regression NeurIPS 2024 Monotonic Risk Relationships under Distribution Shifts for Regularized Risk Minimization JMLR 2024 More PAC-Bayes bounds: From bounded losses, to losses with general tail behaviors, to anytime validity JMLR 2024 More than Just Statistical Recurrence: Human and Machine Unsupervised Learning of Māori Word Segmentation across Morphological Processes NAACL 2024 Motion Capture Analysis of Verb and Adjective Types in Austrian Sign Language (ÖGS) COLING 2024 Muffin or Chihuahua? Challenging Multimodal Large Language Models with Multipanel VQA ACL 2024 Multi-class Probabilistic Bounds for Majority Vote Classifiers with Partially Labeled Data JMLR 2024 Multi-modal conformal prediction regions by optimizing convex shape templates L4DC 2024 Multimodal Learning Without Labeled Multimodal Data: Guarantees and Applications ICLR 2024 Multi-model Ensemble Conformal Prediction in Dynamic Environments NeurIPS 2024 Multi-Response Linear Discriminant Analysis in High Dimensions JMLR 2024 Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics NeurIPS 2024 Near-Interpolators: Rapid Norm Growth and the Trade-Off between Interpolation and Generalization AISTATS 2024 Near-Optimality of Contrastive Divergence Algorithms NeurIPS 2024 Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization ICLR 2024 Neural network learns low-dimensional polynomials with SGD near the information-theoretic limit NeurIPS 2024