Statistical Learning

Humanly Certifying Superhuman Classifiers ICLR 2023 Hypothesis Transfer Learning with Surrogate Classification Losses: Generalization Bounds through Algorithmic Stability ICML 2023 Identifying Selection Bias from Observational Data AAAI 2023 Implicit Regularization in Over-Parameterized Support Vector Machine NeurIPS 2023 Implicit Regularization Leads to Benign Overfitting for Sparse Linear Regression ICML 2023 Improved Policy Evaluation for Randomized Trials of Algorithmic Resource Allocation ICML 2023 Improving Adaptive Conformal Prediction Using Self-Supervised Learning AISTATS 2023 Improving Expert Predictions with Conformal Prediction ICML 2023 Indirectly Supervised Natural Language Processing ACL 2023 Inference for Gaussian Processes with Matern Covariogram on Compact Riemannian Manifolds JMLR 2023 Inference on Strongly Identified Functionals of Weakly Identified Functions COLT 2023 Inference on the Change Point under a High Dimensional Covariance Shift JMLR 2023 Influence Diagnostics under Self-concordance AISTATS 2023 Influence Scores at Scale for Efficient Language Data Sampling EMNLP 2023 Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise COLT 2023 Information Geometry of the Retinal Representation Manifold NeurIPS 2023 Information Theoretic Lower Bounds for Information Theoretic Upper Bounds NeurIPS 2023 Initialization-Dependent Sample Complexity of Linear Predictors and Neural Networks NeurIPS 2023 In- or out-of-distribution detection via dual divergence estimation UAI 2023 In Search of Insights, Not Magic Bullets: Towards Demystification of the Model Selection Dilemma in Heterogeneous Treatment Effect Estimation ICML 2023 Instance-Dependent Confidence and Early Stopping for Reinforcement Learning JMLR 2023 Instance-Dependent Generalization Bounds via Optimal Transport JMLR 2023 Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games AISTATS 2023 Integrating Prior Knowledge in Contrastive Learning with Kernel ICML 2023 Intensity Profile Projection: A Framework for Continuous-Time Representation Learning for Dynamic Networks NeurIPS 2023