Cover Image

Iterative Refinement for $\ell_p$-norm Regression

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Adil, Deeksha, Kyng, Rasmus, Peng, Richard, Sachdeva, Sushant
Format:	Preprint
Published:	2019
Subjects:	Data Structures and Algorithms Numerical Analysis Optimization and Control Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Acceleration Meets Inverse Maintenance: Faster $\ell_{\infty}$-Regression
by: Adil, Deeksha, et al.
Published: (2024)

Fine-grained Analysis and Faster Algorithms for Iteratively Solving Linear Systems
by: Dereziński, Michał, et al.
Published: (2024)

Convex optimization with $p$-norm oracles
by: Adil, Deeksha, et al.
Published: (2024)

Randomized Kaczmarz Methods with Beyond-Krylov Convergence
by: Dereziński, Michał, et al.
Published: (2025)

Approaching Optimality for Solving Dense Linear Systems with Low-Rank Structure
by: Dereziński, Michał, et al.
Published: (2025)

Towards Universal Convergence of Backward Error in Linear System Solvers
by: Dereziński, Michał, et al.
Published: (2026)

Faster Linear Systems and Matrix Norm Approximation via Multi-level Sketched Preconditioning
by: Dereziński, Michał, et al.
Published: (2024)

Solving Dense Linear Systems Faster Than via Preconditioning
by: Dereziński, Michał, et al.
Published: (2023)

Improved $\ell_{p}$ Regression via Iteratively Reweighted Least Squares
by: Ene, Alina, et al.
Published: (2025)

Coresets for Multiple $\ell_p$ Regression
by: Woodruff, David P., et al.
Published: (2024)

Near-Linear Runtime for a Classical Matrix Preconditioning Algorithm
by: Cai, Xufeng, et al.
Published: (2025)

The matrix-vector complexity of $Ax=b$
by: Dereziński, Michał, et al.
Published: (2026)

Balancing Gradient and Hessian Queries in Non-Convex Optimization
by: Adil, Deeksha, et al.
Published: (2025)

On Smale's 17th problem over the reals
by: Montanari, Andrea, et al.
Published: (2024)

Complexity of Classical Acceleration for $\ell_1$-Regularized PageRank
by: Fountoulakis, Kimon, et al.
Published: (2026)

Truncated Variance Reduced Value Iteration
by: Jin, Yujia, et al.
Published: (2024)

Optimal Electrical Oblivious Routing on Expanders
by: Florescu, Cella, et al.
Published: (2024)

Online Correlation Clustering: Simultaneously Optimizing All $\ell_p$-norms
by: Davies, Sami, et al.
Published: (2025)

Sharper Bounds for $\ell_p$ Sensitivity Sampling
by: Woodruff, David P., et al.
Published: (2023)

Turnstile $\ell_p$ leverage score sampling with applications
by: Munteanu, Alexander, et al.
Published: (2024)

Optimal bounds for $\ell_p$ sensitivity sampling via $\ell_2$ augmentation
by: Munteanu, Alexander, et al.
Published: (2024)

Ridge Leverage Score Sampling for $\ell_p$ Subspace Approximation
by: Woodruff, David P., et al.
Published: (2024)

Learning-Augmented Algorithms for the Bahncard Problem
by: Zhao, Hailiang, et al.
Published: (2024)

Efficient and Provable Algorithms for Covariate Shift
by: Adil, Deeksha, et al.
Published: (2025)

Gradient Testing and Estimation by Comparisons
by: Tao, Xiwen, et al.
Published: (2024)

Learning to Schedule in Parallel-Server Queues with Stochastic Bilinear Rewards
by: Kim, Jung-hun, et al.
Published: (2021)

Constrained and Composite Sampling via Proximal Sampler
by: Dang, Thanh, et al.
Published: (2026)

Importance Sparsification for Sinkhorn Algorithm
by: Li, Mengyu, et al.
Published: (2023)

Optimal Bounds for Adversarial Constrained Online Convex Optimization
by: Ferreira, Ricardo N., et al.
Published: (2025)

Min-Max Optimization Is Strictly Easier Than Variational Inequalities
by: Shugart, Henry, et al.
Published: (2025)

Robust Learning of a Group DRO Neuron
by: Cao, Guyang, et al.
Published: (2026)

Online Linear Programming with Replenishment
by: Chen, Yuze, et al.
Published: (2026)

Learning-Augmented Algorithms for Online Concave Packing and Convex Covering Problems
by: Grigorescu, Elena, et al.
Published: (2024)

Learning Mixtures of Spherical Gaussians via Fourier Analysis
by: Chakraborty, Somnath, et al.
Published: (2020)

Negative Stepsizes Make Gradient-Descent-Ascent Converge
by: Shugart, Henry, et al.
Published: (2025)

Gaussian Cooling and Dikin Walks: The Interior-Point Method for Logconcave Sampling
by: Kook, Yunbum, et al.
Published: (2023)

Noise Stability Optimization for Finding Flat Minima: A Hessian-based Regularization Approach
by: Zhang, Hongyang R., et al.
Published: (2023)

Closing the Computational-Query Depth Gap in Parallel Stochastic Convex Optimization
by: Jambulapati, Arun, et al.
Published: (2024)

Online Bilevel Optimization: Regret Analysis of Online Alternating Gradient Methods
by: Tarzanagh, Davoud Ataee, et al.
Published: (2022)

Non-Stationary Online Resource Allocation: Learning from a Single Sample
by: Feng, Yiding, et al.
Published: (2026)