Statistical Learning

Covariate Shift Corrected Conditional Randomization Test NeurIPS 2024 Coverage-Guaranteed Prediction Sets for Out-of-Distribution Data AAAI 2024 Credal Learning Theory NeurIPS 2024 Credit Attribution and Stable Compression NeurIPS 2024 Critical Gap Between Generalization Error and Empirical Error in Active Learning WACV 2024 Cross-Linguistic Intelligibility of Non-Compositional Expressions in Spoken Context Interspeech 2024 CryoBench: Diverse and challenging datasets for the heterogeneity problem in cryo-EM NeurIPS 2024 DAGnosis: Localized Identification of Data Inconsistencies using Structures AISTATS 2024 Data Contamination Calibration for Black-box LLMs ACL 2024 Data Distribution Valuation NeurIPS 2024 Data-driven Automated Negative Control Estimation (DANCE): Search for, Validation of, and Causal Inference with Negative Controls JMLR 2024 Data Thinning for Convolution-Closed Distributions JMLR 2024 Debiasing Synthetic Data Generated by Deep Generative Models NeurIPS 2024 Debiasing with Sufficient Projection: A General Theoretical Framework for Vector Representations NAACL 2024 Deciphering 'What' and 'Where' Visual Pathways from Spectral Clustering of Layer-Distributed Neural Representations CVPR 2024 Decoding Human Language Acquisition: EEG Evidence for Predictive Probabilistic Statistics in Word Segmentation Interspeech 2024 Decorrelated Variable Importance JMLR 2024 Deep anytime-valid hypothesis testing AISTATS 2024 Deep Copula-Based Survival Analysis for Dependent Censoring with Identifiability Guarantees AAAI 2024 DeepDRK: Deep Dependency Regularized Knockoff for Feature Selection NeurIPS 2024 Deeper or Wider: A Perspective from Optimal Generalization Error with Sobolev Loss ICML 2024 DeepFDR: A Deep Learning-based False Discovery Rate Control Method for Neuroimaging Data AISTATS 2024 Deep Metric Learning With Chance Constraints WACV 2024 Depth Separation in Norm-Bounded Infinite-Width Neural Networks COLT 2024 Derandomizing Multi-Distribution Learning NeurIPS 2024