least square

Deep Iterative Surface Normal Estimation CVPR 2020 Implicit Regularization and Convergence for Weight Normalization NeurIPS 2020 MAGSAC++, a Fast, Reliable and Accurate Robust Estimator CVPR 2020 Minimax Rank-$1$ Matrix Factorization AISTATS 2020 Minimax Rate for Learning From Pairwise Comparisons in the BTL Model ICML 2020 No-Regret Prediction in Marginally Stable Systems COLT 2020 On Suboptimality of Least Squares with Application to Estimation of Convex Bodies COLT 2020 Optimal Iterative Sketching Methods with the Subsampled Randomized Hadamard Transform NeurIPS 2020 Optimal least-squares solution to the hand-eye calibration problem CVPR 2020 Quasi-Newton Solver for Robust Non-Rigid Registration CVPR 2020 Sobolev Norm Learning Rates for Regularized Least-Squares Algorithms JMLR 2020 The Implicit Regularization of Stochastic Gradient Flow for Least Squares ICML 2020 Uncorrected Least-Squares Temporal Difference with Lambda-Return AAAI 2020 Correcting the bias in least squares regression with volume-rescaled sampling AISTATS 2019 DINGO: Distributed Newton-Type Method for Gradient-Norm Optimization NeurIPS 2019 Fast and Accurate Least-Mean-Squares Solvers NeurIPS 2019 Implicit Regularization of Accelerated Methods in Hilbert Spaces NeurIPS 2019 Learning Linear Dynamical Systems with Semi-Parametric Least Squares COLT 2019 Near optimal finite time identification of arbitrary linear dynamical systems ICML 2019 The Step Decay Schedule: A Near Optimal, Geometrically Decaying Learning Rate Procedure For Least Squares NeurIPS 2019 Cause-Effect Inference by Comparing Regression Errors AISTATS 2018 Error Estimation for Randomized Least-Squares Algorithms via the Bootstrap ICML 2018 Learning To Learn Around A Common Mean NeurIPS 2018 Reverse Iterative Volume Sampling for Linear Regression JMLR 2018 A Non-Convex Variational Approach to Photometric Stereo Under Inaccurate Lighting CVPR 2017