← Optimization & Theory
Machine Learning › Optimization & Theory ›

Statistical Learning

4076 directly classified papers

Papers per year

Papers

Data-Driven Subgroup Identification for Linear Regression ICML 2023
Data-Driven Invariant Learning for Probabilistic Programs (Extended Abstract) IJCAI 2023
The Price of Differential Privacy under Continual Observation ICML 2023
On the Statistical Benefits of Temporal Difference Learning ICML 2023
Learning Robust Representations with Information Bottleneck and Memory Network for RGB-D-based Gesture Recognition ICCV 2023
Hierarchical Visual Categories Modeling: A Joint Representation Learning and Density Estimation Framework for Out-of-Distribution Detection ICCV 2023
On the Reuse Bias in Off-Policy Reinforcement Learning IJCAI 2023
Learning Functional Distributions with Private Labels ICML 2023
Proper Scoring Rules for Survival Analysis ICML 2023
The Geometry and Calculus of Losses JMLR 2023
More for Less: Safe Policy Improvement with Stronger Performance Guarantees IJCAI 2023
SAT-Based PAC Learning of Description Logic Concepts IJCAI 2023
On Second-Order Scoring Rules for Epistemic Uncertainty Quantification ICML 2023
Towards Understanding Generalization of Macro-AUC in Multi-label Learning ICML 2023
Are Gaussian Data All You Need? The Extents and Limits of Universality in High-Dimensional Generalized Linear Estimation ICML 2023
On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits ICML 2023
Thompson Sampling for High-Dimensional Sparse Linear Contextual Bandits ICML 2023
Learning Survival Distribution with Implicit Survival Function IJCAI 2023
Scalable Optimal Margin Distribution Machine IJCAI 2023
Accuracy on the Curve: On the Nonlinear Correlation of ML Performance Between Data Subpopulations ICML 2023
Differential Privacy has Bounded Impact on Fairness in Classification ICML 2023
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts ICML 2023
Nonparametric Density Estimation under Distribution Drift ICML 2023
Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting ICML 2023
Biases in Evaluation of Molecular Optimization Methods and Bias Reduction Strategies ICML 2023