← Authors

Haim Avron

19 papers · 2013–2024 · 4 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (14) 🧭 Keyword Pioneer 🌍 Conference Polyglot (4) πŸƒ Academic Marathon (11) 🐝 Cross-Pollinator (13) πŸ† Keyword Champion (2) πŸ—ƒοΈ Keyword Collector (83) πŸ”₯ Unstoppable (6) πŸš€ Conference Pioneer πŸ’Ž Century Club (19) πŸ“ˆ Trend Setter

Conferences

ICML (7) NIPS (6) JMLR (5) CVPR (1)

Top co-authors

Insu Han (5) Vikas Sindhwani (5) Amir Zandieh (4) Jinwoo Shin (3) Petros Drineas (3) Agniva Chowdhury (3) Jiyan Yang (3) Palma London (2) Gregory Dexter (2) David Woodruff (2)

Keywords

kernel methods (7) kernel approximation (4) random feature (3) linear programming (3) interior point method (3) low-discrepancy sequence (2) low-rank approximation (2) quasi-monte carlo (2) randomized algorithm (2) feature map (2) matrix sketching (2) kernel regression (2) randomized linear algebra (2) shift-invariant kernel (2) neural tangent kernel (2) kernel ridge regression (2) conjugate gradient (2) numerical linear algebra (2) random fourier feature (2) signal reconstruction (1)

Papers

Faster Randomized Methods for Orthogonality Constrained Problems JMLR 2024
Near Optimal Reconstruction of Spherical Harmonic Expansions NIPS 2023
On the Convergence of Inexact Predictor-Corrector Methods for Linear Programming ICML 2022
Faster Randomized Interior Point Methods for Tall/Wide Linear Programs JMLR 2022
Gauss-Legendre Features for Gaussian Process Regression JMLR 2022
Random Gegenbauer Features for Scalable Kernel Methods ICML 2022
Scaling Neural Tangent Kernels via Sketching and Random Features NIPS 2021
Polynomial Tensor Sketch for Element-wise Function of Low-Rank Matrix ICML 2020
Faster Randomized Infeasible Interior Point Methods for Tall/Wide Linear Programs NIPS 2020
Stochastic Chebyshev Gradient Descent for Spectral Optimization NIPS 2018
Hierarchically Compositional Kernels for Scalable Nonparametric Learning JMLR 2017
Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees ICML 2017
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels JMLR 2016
Community Detection Using Time-Dependent Personalized PageRank ICML 2015
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels ICML 2014
Random Laplace Feature Maps for Semigroup Kernels on Histograms CVPR 2014
Subspace Embeddings for the Polynomial Kernel NIPS 2014
Sketching Structured Matrices for Faster Nonlinear Regression NIPS 2013
Efficient Dimensionality Reduction for Canonical Correlation Analysis ICML 2013