least squares regression

Sobolev Norm Learning Rates for Regularized Least-Squares Algorithms JMLR 2020 Uncorrected Least-Squares Temporal Difference with Lambda-Return AAAI 2020 A Continuous-Time View of Early Stopping for Least Squares Regression AISTATS 2019 Asymptotics for Sketching in Least Squares Regression NeurIPS 2019 Implicit Regularization for Optimal Sparse Recovery NeurIPS 2019 Minimax experimental design: Bridging the gap between statistical and worst-case approaches to least squares regression COLT 2019 Sublinear Time Numerical Linear Algebra for Structured Matrices AAAI 2019 Accelerating Stochastic Gradient Descent for Least Squares Regression COLT 2018 Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces ICML 2018 Parallelizing Stochastic Gradient Descent for Least Squares Regression: Mini-batching, Averaging, and Model Misspecification JMLR 2018 Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes NeurIPS 2018 Adaptive Semi-Supervised Learning with Discriminative Least Squares Regression IJCAI 2017 An inner-loop free solution to inverse problems using deep neural networks NeurIPS 2017 Deep Least Squares Regression for Speaker Adaptation Interspeech 2017 Encrypted Accelerated Least Squares Regression AISTATS 2017 Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression JMLR 2017 Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks ICML 2017 Prio: Private, Robust, and Scalable Computation of Aggregate Statistics NSDI 2017 Robust Regression via Heuristic Hard Thresholding IJCAI 2017 Stochastic Composite Least-Squares Regression with Convergence Rate $O(1/n)$ COLT 2017 Loss Minimization and Parameter Estimation with Heavy Tails JMLR 2016 NYTRO: When Subsampling Meets Early Stopping AISTATS 2016 Averaged Least-Mean-Squares: Bias-Variance Trade-offs and Optimal Sampling Distributions AISTATS 2015 Learning Theory of Randomized Kaczmarz Algorithm JMLR 2015 A Gaussian Latent Variable Model for Large Margin Classification of Labeled and Unlabeled Data AISTATS 2014