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Statistical Learning

4,117 papers

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Papers

Towards Costless Model Selection in Contextual Bandits: A Bias-Variance Perspective AISTATS 2024
DNNLasso: Scalable Graph Learning for Matrix-Variate Data AISTATS 2024
Empirical Design in Reinforcement Learning JMLR 2024
On Differentially Private Subspace Estimation in a Distribution-Free Setting NIPS 2024
Non-parametric classification via expand-and-sparsify representation NIPS 2024
Dimension-free deterministic equivalents and scaling laws for random feature regression NIPS 2024
Test-Time Linear Out-of-Distribution Detection CVPR 2024
Do we EXPECT TO find phonetic traces for syntactic traces? INTERSPEECH 2024
Graph Classification via Reference Distribution Learning: Theory and Practice NIPS 2024
On the Stability and Generalization of Meta-Learning NIPS 2024
On the Connection between Lp- and Risk Consistency and its Implications on Regularized Kernel Methods JMLR 2024
Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance JMLR 2024
Adaptive Learning of Density Ratios in RKHS JMLR 2023
Probabilistically robust conformal prediction UAI 2023
A Generalized Unbiased Risk Estimator for Learning with Augmented Classes AAAI 2023
The Geometry and Calculus of Losses JMLR 2023
Robust Data Valuation with Weighted Banzhaf Values NIPS 2023
Average Adjusted Association: Efficient Estimation with High Dimensional Confounders AISTATS 2023
Faithful Model Evaluation for Model-Based Metrics EMNLP 2023
Cross-Entropy Loss Functions: Theoretical Analysis and Applications ICML 2023
Federated Asymptotics: a model to compare federated learning algorithms AISTATS 2023
Validation of a Task-Independent Cepstral Peak Prominence Measure with Voice Activity Detection INTERSPEECH 2023
Distributed Statistical Inference under Heterogeneity JMLR 2023
PED-ANOVA: Efficiently Quantifying Hyperparameter Importance in Arbitrary Subspaces IJCAI 2023
Adaptive Principal Component Regression with Applications to Panel Data NIPS 2023