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Statistical Learning

4,117 papers

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Papers

Kernel QuantTree ICML 2023
Functional L-Optimality Subsampling for Functional Generalized Linear Models with Massive Data JMLR 2023
Is interpolation benign for random forest regression? AISTATS 2023
Conformalized Unconditional Quantile Regression AISTATS 2023
Evaluating Generative Networks Using Gaussian Mixtures of Image Features WACV 2023
Inference for Gaussian Processes with Matern Covariogram on Compact Riemannian Manifolds JMLR 2023
Tensor Decompositions Meet Control Theory: Learning General Mixtures of Linear Dynamical Systems ICML 2023
T-Cal: An Optimal Test for the Calibration of Predictive Models JMLR 2023
Shortest Program Interpolation Learning COLT 2023
Contrasting Identifying Assumptions of Average Causal Effects: Robustness and Semiparametric Efficiency JMLR 2023
Dimensionless machine learning: Imposing exact units equivariance JMLR 2023
Randomized Spectral Co-Clustering for Large-Scale Directed Networks JMLR 2023
Explainability as statistical inference ICML 2023
Spatio-Temporal Neural Structural Causal Models for Bike Flow Prediction AAAI 2023
Leveraging Inter-Rater Agreement for Classification in the Presence of Noisy Labels CVPR 2023
An Ordinal Latent Variable Model of Conflict Intensity ACL 2023
Building Persona Consistent Dialogue Agents with Offline Reinforcement Learning EMNLP 2023
Asymptotics of Network Embeddings Learned via Subsampling JMLR 2023
Classification of Heavy-tailed Features in High Dimensions: a Superstatistical Approach NIPS 2023
Learning Curves for Deep Structured Gaussian Feature Models NIPS 2023
Shedding a PAC-Bayesian Light on Adaptive Sliced-Wasserstein Distances ICML 2023
High-dimensional Location Estimation via Norm Concentration for Subgamma Vectors ICML 2023
Using Sliced Mutual Information to Study Memorization and Generalization in Deep Neural Networks AISTATS 2023
Neural FIM for learning Fisher information metrics from point cloud data ICML 2023
Bootstrap in High Dimension with Low Computation ICML 2023