Regression

On Least Square Estimation in Softmax Gating Mixture of Experts ICML 2024 Online Infinite-Dimensional Regression: Learning Linear Operators ALT 2024 On Parameter Estimation in Deviated Gaussian Mixture of Experts AISTATS 2024 On Tail Decay Rate Estimation of Loss Function Distributions JMLR 2024 On the Computational Complexity of Private High-dimensional Model Selection NeurIPS 2024 On the Efficiency of ERM in Feature Learning NeurIPS 2024 On the Lasso for Graphical Continuous Lyapunov Models CLeaR 2024 On the Misspecification of Linear Assumptions in Synthetic Controls AISTATS 2024 On the Optimality of Misspecified Spectral Algorithms JMLR 2024 On the relationship between speech production and vocabulary size in 3-5 year olds Interspeech 2024 On the Role of Context in Reading Time Prediction EMNLP 2024 On the sample complexity of parameter estimation in logistic regression with normal design COLT 2024 On the Target-kernel Alignment: a Unified Analysis with Kernel Complexity NeurIPS 2024 On Using Admissible Bounds for Learning Forward Search Heuristics IJCAI 2024 Optimal Aggregation of Prediction Intervals under Unsupervised Domain Shift NeurIPS 2024 Optimal criterion for feature learning of two-layer linear neural network in high dimensional interpolation regime ICLR 2024 Optimal Kernel Quantile Learning with Random Features ICML 2024 Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms NeurIPS 2024 Optimal Ridge Regularization for Out-of-Distribution Prediction ICML 2024 Optimal Weighted Random Forests JMLR 2024 Orthogonal Gradient Boosting for Simpler Additive Rule Ensembles AISTATS 2024 Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift ICML 2024 Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality NeurIPS 2024 PACE: Pacing Operator Learning to Accurate Optical Field Simulation for Complicated Photonic Devices NeurIPS 2024 PAGER: Accurate Failure Characterization in Deep Regression Models ICML 2024