Drineas, Petros

26 publications

ICML 2025 Stacey: Promoting Stochastic Steepest Descent via Accelerated $\ell_p$-Smooth Nonconvex Optimization Xinyu Luo, Site Bai, Bolian Li, Petros Drineas, Ruqi Zhang, Brian Bullins

NeurIPS 2025 Structure-Aware Spectral Sparsification via Uniform Edge Sampling Kaiwen He, Petros Drineas, Rajiv Khanna

CVPR 2024 Patch2Self2: Self-Supervised Denoising on Coresets via Matrix Sketching Shreyas Fadnavis, Agniva Chowdhury, Joshua Batson, Petros Drineas, Eleftherios Garyfallidis

NeurIPS 2024 The Space Complexity of Approximating Logistic Loss Gregory Dexter, Petros Drineas, Rajiv Khanna

NeurIPS 2023 Refined Mechanism Design for Approximately Structured Priors via Active Regression Christos Boutsikas, Petros Drineas, Marios Mertzanidis, Alexandros Psomas, Paritosh Verma

NeurIPS 2023 Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming Gregory Dexter, Petros Drineas, David Woodruff, Taisuke Yasuda

JMLR 2022 Faster Randomized Interior Point Methods for Tall/Wide Linear Programs Agniva Chowdhury, Gregory Dexter, Palma London, Haim Avron, Petros Drineas

ICML 2022 On the Convergence of Inexact Predictor-Corrector Methods for Linear Programming Gregory Dexter, Agniva Chowdhury, Haim Avron, Petros Drineas

NeurIPS 2020 Faster Randomized Infeasible Interior Point Methods for Tall/Wide Linear Programs Agniva Chowdhury, Palma London, Haim Avron, Petros Drineas

UAI 2019 Randomized Iterative Algorithms for Fisher Discriminant Analysis Agniva Chowdhury, Jiasen Yang, Petros Drineas

ICML 2018 An Iterative, Sketching-Based Framework for Ridge Regression Agniva Chowdhury, Jiasen Yang, Petros Drineas

JMLR 2017 Recovering PCA and Sparse PCA via Hybrid-(l1,l2) Sparse Sampling of Data Elements Abhisek Kundu, Petros Drineas, Malik Magdon-Ismail

NeurIPS 2015 Approximating Sparse PCA from Incomplete Data Abhisek Kundu, Petros Drineas, Malik Magdon-Ismail

NeurIPS 2015 Column Selection via Adaptive Sampling Saurabh Paul, Malik Magdon-Ismail, Petros Drineas

AISTATS 2015 Feature Selection for Linear SVM with Provable Guarantees Saurabh Paul, Malik Magdon-Ismail, Petros Drineas

ECML-PKDD 2014 Deterministic Feature Selection for Regularized Least Squares Classification Saurabh Paul, Petros Drineas

AISTATS 2013 Random Projections for Support Vector Machines Saurabh Paul, Christos Boutsidis, Malik Magdon-Ismail, Petros Drineas

JMLR 2012 Fast Approximation of Matrix Coherence and Statistical Leverage Petros Drineas, Malik Magdon-Ismail, Michael W. Mahoney, David P. Woodruff

ICML 2012 Fast Approximation of Matrix Coherence and Statistical Leverage Michael W. Mahoney, Petros Drineas, Malik Magdon-Ismail, David P. Woodruff

NeurIPS 2011 Sparse Features for PCA-like Linear Regression Christos Boutsidis, Petros Drineas, Malik Magdon-Ismail

NeurIPS 2010 Random Projections for $k$-Means Clustering Christos Boutsidis, Anastasios Zouzias, Petros Drineas

NeurIPS 2009 Unsupervised Feature Selection for the $k$-Means Clustering Problem Christos Boutsidis, Petros Drineas, Michael W. Mahoney

COLT 2005 Approximating a Gram Matrix for Improved Kernel-Based Learning Petros Drineas, Michael W. Mahoney

CVPR 2005 Energy Minimization via Graph Cuts: Settling What Is Possible Daniel Freedman, Petros Drineas

JMLR 2005 On the Nystrom Method for Approximating a Gram Matrix for Improved Kernel-Based Learning Petros Drineas, Michael W. Mahoney

MLJ 2004 Clustering Large Graphs via the Singular Value Decomposition Petros Drineas, Alan M. Frieze, Ravi Kannan, Santosh S. Vempala, V. Vinay