Petros Drineas
20 papers · 2005–2025 · 6 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (6) π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (14) π Interdisciplinary Bridge π Academic Marathon (20)
π§
Keyword Pioneer
π
Cross-Pollinator
(10)
π
Conference Polyglot
(6)
π
Keyword Trendsetter Combo
(4)
π
Keyword Champion
π₯
Unstoppable
(5)
π
Century Club
(20)
ποΈ
Keyword Collector
(83)
π
Trend Setter
π
Conference Pioneer
Conferences
NIPS (9)
JMLR (4)
ICML (3)
AISTATS (2)
CVPR (1)
UAI (1)
Top co-authors
Research topics
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