least squares regression

LS-ViT: Least-Squares Hessian Based Block Reconstruction for Low-Bit Post-Training Quantization of Vision Transformers CVPR 2026 Computationally Efficient RL under Linear Bellman Completeness for Deterministic Dynamics ICLR 2025 Error dynamics of mini-batch gradient descent with random reshuffling for least squares regression ALT 2025 Compressed and distributed least-squares regression: convergence rates with applications to federated learning JMLR 2024 Distributed Least Squares in Small Space via Sketching and Bias Reduction NeurIPS 2024 Failures and Successes of Cross-Validation for Early-Stopped Gradient Descent AISTATS 2024 Faster Approximation of Probabilistic and Distributional Values via Least Squares ICLR 2024 Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares Extended Abstract COLT 2024 Least Squares Regression Can Exhibit Under-Parameterized Double Descent NeurIPS 2024 Mitigating Covariate Shift in Misspecified Regression with Applications to Reinforcement Learning COLT 2024 Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation ICML 2024 Efficient Top-K Feature Selection Using Coordinate Descent Method AAAI 2023 Hyperparameter Tuning of an Off-Policy Reinforcement Learning Algorithm for H∞ Tracking Control L4DC 2023 Accelerated SGD for Non-Strongly-Convex Least Squares COLT 2022 Learning Sparse Fixed-Structure Gaussian Bayesian Networks AISTATS 2022 Least Squares Estimation using Sketched Data with Heteroskedastic Errors ICML 2022 Scale-free Unconstrained Online Learning for Curved Losses COLT 2022 Vector-Valued Least-Squares Regression under Output Regularity Assumptions JMLR 2022 Gradient Descent in RKHS with Importance Labeling AISTATS 2021 In-Database Regression in Input Sparsity Time ICML 2021 Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections JMLR 2020 Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms NeurIPS 2020 On Coresets for Regularized Regression ICML 2020 Optimal Learning from Verified Training Data NeurIPS 2020 Optimal Randomized First-Order Methods for Least-Squares Problems ICML 2020