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Petros Drineas

20 papers · 2005–2025 · 6 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (20) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (14) 🌈 Renaissance Researcher (7) 🧭 Keyword Pioneer 🐝 Cross-Pollinator (10) 🌍 Conference Polyglot (6) 🌟 Keyword Trendsetter Combo (4) πŸ† Keyword Champion πŸ”₯ Unstoppable (5) πŸ’Ž Century Club (20) πŸ—ƒοΈ Keyword Collector (83) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer

Conferences

NIPS (9) JMLR (4) ICML (3) AISTATS (2) CVPR (1) UAI (1)

Top co-authors

Malik Magdon-Ismail (7) Agniva Chowdhury (6) Christos Boutsidis (4) Gregory Dexter (4) Michael W. Mahoney (3) Haim Avron (3) Saurabh Paul (3) Palma London (2) ABHISEK KUNDU (2) Jiasen Yang (2)

Research topics

Statistics (1)

Keywords

matrix sketching (5) randomized linear algebra (4) dimensionality reduction (4) randomized algorithm (4) k-means clustering (3) low-rank approximation (3) linear programming (3) interior point method (3) leverage score (2) random projection (2) relative error (2) feature selection (2) approximation algorithm (2) matrix factorization (2) matrix completion (2) nystrom method (2) margin maximization (2) dimension reduction (2) sparse principal component analysis (2) conjugate gradient (2)

Papers

Stacey: Promoting Stochastic Steepest Descent via Accelerated $\ell_p$-Smooth Nonconvex Optimization ICML 2025
Patch2Self2: Self-supervised Denoising on Coresets via Matrix Sketching CVPR 2024
The Space Complexity of Approximating Logistic Loss NIPS 2024
Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming NIPS 2023
Refined Mechanism Design for Approximately Structured Priors via Active Regression 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
Faster Randomized Infeasible Interior Point Methods for Tall/Wide Linear Programs NIPS 2020
Randomized Iterative Algorithms for Fisher Discriminant Analysis UAI 2019
An Iterative, Sketching-based Framework for Ridge Regression ICML 2018
Recovering PCA and Sparse PCA via Hybrid-(l1,l2) Sparse Sampling of Data Elements JMLR 2017
Feature Selection for Linear SVM with Provable Guarantees AISTATS 2015
Approximating Sparse PCA from Incomplete Data NIPS 2015
Column Selection via Adaptive Sampling NIPS 2015
Random Projections for Support Vector Machines AISTATS 2013
Fast Approximation of Matrix Coherence and Statistical Leverage JMLR 2012
Sparse Features for PCA-Like Linear Regression NIPS 2011
Random Projections for $k$-means Clustering NIPS 2010
Unsupervised Feature Selection for the $k$-means Clustering Problem NIPS 2009
On the Nystrom Method for Approximating a Gram Matrix for Improved Kernel-Based Learning JMLR 2005