Statistical Learning

Cross-Entropy Loss Functions: Theoretical Analysis and Applications ICML 2023 DART: Distance Assisted Recursive Testing JMLR 2023 Data-Driven Invariant Learning for Probabilistic Programs (Extended Abstract) IJCAI 2023 Data-Driven Subgroup Identification for Linear Regression ICML 2023 Data-OOB: Out-of-bag Estimate as a Simple and Efficient Data Value ICML 2023 DataPerf: Benchmarks for Data-Centric AI Development NeurIPS 2023 Data Structures for Density Estimation ICML 2023 DE-CROP: Data-Efficient Certified Robustness for Pretrained Classifiers WACV 2023 Deep Generative Modeling on Limited Data with Regularization by Nontransferable Pre-trained Models ICLR 2023 Demystifying Disagreement-on-the-Line in High Dimensions ICML 2023 Demystifying Softmax Gating Function in Gaussian Mixture of Experts NeurIPS 2023 Demystifying the Optimal Performance of Multi-Class Classification NeurIPS 2023 Density Ratio Estimation and Neyman Pearson Classification with Missing Data AISTATS 2023 Derandomized novelty detection with FDR control via conformal e-values NeurIPS 2023 DetAIL: A Tool to Automatically Detect and Analyze Drift in Language AAAI 2023 Detecting Edit Failures In Large Language Models: An Improved Specificity Benchmark ACL 2023 Detection-Recovery Gap for Planted Dense Cycles COLT 2023 Deterministic equivalent and error universality of deep random features learning ICML 2023 DIET: Conditional independence testing with marginal dependence measures of residual information AISTATS 2023 Differentially Private Hypothesis Testing for Linear Regression JMLR 2023 Differential Privacy has Bounded Impact on Fairness in Classification ICML 2023 Diffusion Models are Minimax Optimal Distribution Estimators ICML 2023 Dimensionless machine learning: Imposing exact units equivariance JMLR 2023 Distance-to-Set Priors and Constrained Bayesian Inference AISTATS 2023 Distributed Nonparametric Regression Imputation for Missing Response Problems with Large-scale Data JMLR 2023