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Statistical Learning

4076 directly classified papers

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Papers

Stochastic Approximation with Decision-Dependent Distributions: Asymptotic Normality and Optimality JMLR 2024
Credit Attribution and Stable Compression NIPS 2024
Hardness of Learning Neural Networks under the Manifold Hypothesis NIPS 2024
Online Estimation via Offline Estimation: An Information-Theoretic Framework NIPS 2024
Distributionally Robust Performative Prediction NIPS 2024
Logistic Regression Under Network Dependence JMLR 2024
Great Minds Think Alike: The Universal Convergence Trend of Input Salience NIPS 2024
SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification AISTATS 2024
Universal Rates for Active Learning NIPS 2024
Working Memory Capacity of ChatGPT: An Empirical Study AAAI 2024
Identifying Causal Effects Under Functional Dependencies NIPS 2024
Measuring Multimodal Mathematical Reasoning with MATH-Vision Dataset NIPS 2024
Multi-modal conformal prediction regions by optimizing convex shape templates L4DC 2024
Iterate Averaging in the Quest for Best Test Error JMLR 2024
Universally Instance-Optimal Mechanisms for Private Statistical Estimation COLT 2024
Computational-Statistical Gaps for Improper Learning in Sparse Linear Regression COLT 2024
DNNLasso: Scalable Graph Learning for Matrix-Variate Data AISTATS 2024
Online Distribution Learning with Local Privacy Constraints AISTATS 2024
Minimax optimal density estimation using a shallow generative model with a one-dimensional latent variable AISTATS 2024
Clustering Items From Adaptively Collected Inconsistent Feedback AISTATS 2024
Deep anytime-valid hypothesis testing AISTATS 2024
Randomized algorithms and PAC bounds for inverse reinforcement learning in continuous spaces NIPS 2024
Generalization Bounds of Nonconvex-(Strongly)-Concave Stochastic Minimax Optimization AISTATS 2024
Asymptotic Characterisation of the Performance of Robust Linear Regression in the Presence of Outliers AISTATS 2024
Stability and L2-penalty in Model Averaging JMLR 2024