Statistical Learning

Bandit Learnability can be Undecidable COLT 2023 Batch Multivalid Conformal Prediction ICLR 2023 Bayesian Data Selection JMLR 2023 Bayesian Oracle for bounding information gain in neural encoding models ICLR 2023 Bayesian Spiked Laplacian Graphs JMLR 2023 Bayesian Strategy-Proof Facility Location via Robust Estimation AISTATS 2023 Bayesian Variable Selection in a Million Dimensions AISTATS 2023 Beatboxing Kick Drum Kinematics Interspeech 2023 Benchmarking Distribution Shift in Tabular Data with TableShift NeurIPS 2023 Benign overfitting in ridge regression JMLR 2023 Beyond Normal: On the Evaluation of Mutual Information Estimators NeurIPS 2023 Beyond Performative Prediction: Open-environment Learning with Presence of Corruptions AISTATS 2023 Biases in Evaluation of Molecular Optimization Methods and Bias Reduction Strategies ICML 2023 Bootstrap in High Dimension with Low Computation ICML 2023 Bounding the Family-Wise Error Rate in Local Causal Discovery Using Rademacher Averages (Extended Abstract) IJCAI 2023 Building Persona Consistent Dialogue Agents with Offline Reinforcement Learning EMNLP 2023 Byzantine-Robust Federated Learning with Optimal Statistical Rates AISTATS 2023 Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems ICLR 2023 Can semi-supervised learning use all the data effectively? A lower bound perspective NeurIPS 2023 Causal effect estimation from observational and interventional data through matrix weighted linear estimators UAI 2023 Causal Isotonic Calibration for Heterogeneous Treatment Effects ICML 2023 CausalSim: A Causal Framework for Unbiased Trace-Driven Simulation NSDI 2023 Cause-Effect Inference in Location-Scale Noise Models: Maximum Likelihood vs. Independence Testing NeurIPS 2023 Characterizing Out-of-Distribution Error via Optimal Transport NeurIPS 2023 Class based Influence Functions for Error Detection ACL 2023