# Petros Drineas

According to our database1, Petros Drineas authored at least 107 papers between 1999 and 2020.

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## Bibliography

2020
Randomized Linear Algebra Approaches to Estimate the von Neumann Entropy of Density Matrices.
IEEE Trans. Inf. Theory, 2020

Approximation Algorithms for Sparse Principal Component Analysis.
CoRR, 2020

Speeding up Linear Programming using Randomized Linear Algebra.
CoRR, 2020

CluStrat: A Structure Informed Clustering Strategy for Population Stratification.
Proceedings of the Research in Computational Molecular Biology, 2020

Faster Randomized Infeasible Interior Point Methods for Tall/Wide Linear Programs.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Genetics and Population Analysis.
Proceedings of the Encyclopedia of Bioinformatics and Computational Biology - Volume 3, 2019

Low-Rank Matrix Approximations Do Not Need a Singular Value Gap.
SIAM J. Matrix Anal. Appl., 2019

A randomized least squares solver for terabyte-sized dense overdetermined systems.
J. Comput. Sci., 2019

TeraPCA: a fast and scalable software package to study genetic variation in tera-scale genotypes.
Bioinform., 2019

Randomized Iterative Algorithms for Fisher Discriminant Analysis.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

2018
Structural Convergence Results for Approximation of Dominant Subspaces from Block Krylov Spaces.
SIAM J. Matrix Anal. Appl., 2018

Constructing Compact Brain Connectomes for Individual Fingerprinting.
CoRR, 2018

Near Optimal Linear Algebra in the Online and Sliding Window Models
CoRR, 2018

Randomized Linear Algebra Approaches to Estimate the Von Neumann Entropy of Density Matrices.
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

An Iterative, Sketching-based Framework for Ridge Regression.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
A Randomized Rounding Algorithm for Sparse PCA.
ACM Trans. Knowl. Discov. Data, 2017

Recovering PCA and Sparse PCA via Hybrid-(l1, l2) Sparse Sampling of Data Elements.
J. Mach. Learn. Res., 2017

Lectures on Randomized Numerical Linear Algebra.
CoRR, 2017

Coreset Construction via Randomized Matrix Multiplication.
CoRR, 2017

Variant Ranker: a web-tool to rank genomic data according to functional significance.
BMC Bioinform., 2017

2016
The Fast Cauchy Transform and Faster Robust Linear Regression.
SIAM J. Comput., 2016

Feature selection for linear SVM with provable guarantees.
Pattern Recognit., 2016

Feature Selection for Ridge Regression with Provable Guarantees.
Neural Comput., 2016

Structural Convergence Results for Low-Rank Approximations from Block Krylov Spaces.
CoRR, 2016

RandNLA: randomized numerical linear algebra.
Commun. ACM, 2016

Randomized Sketching for Large-Scale Sparse Ridge Regression Problems.
Proceedings of the 7th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, 2016

Structural Properties Underlying High-Quality Randomized Numerical Linear Algebra Algorithms.
Proceedings of the Handbook of Big Data., 2016

2015
Randomized Dimensionality Reduction for k-Means Clustering.
IEEE Trans. Inf. Theory, 2015

Recovering PCA from Hybrid-(ℓ<sub>1</sub>, ℓ<sub>2</sub>) Sparse Sampling of Data Elements.
CoRR, 2015

A Randomized Rounding Algorithm for Sparse PCA.
CoRR, 2015

A Randomized Algorithm for Approximating the Log Determinant of a Symmetric Positive Definite Matrix.
CoRR, 2015

A scalable randomized least squares solver for dense overdetermined systems.
Proceedings of the 6th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, 2015

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Approximating Sparse PCA from Incomplete Data.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014
Random Projections for Linear Support Vector Machines.
ACM Trans. Knowl. Discov. Data, 2014

Near-Optimal Column-Based Matrix Reconstruction.
SIAM J. Comput., 2014

Deterministic Feature Selection for Linear SVM with Provable Guarantees.
CoRR, 2014

A Note on Randomized Element-wise Matrix Sparsification.
CoRR, 2014

Deterministic Feature Selection for Regularized Least Squares Classification.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

2013
Near-Optimal Coresets for Least-Squares Regression.
IEEE Trans. Inf. Theory, 2013

Random Projections for Support Vector Machines.
Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012
Fast approximation of matrix coherence and statistical leverage.
J. Mach. Learn. Res., 2012

The Fast Cauchy Transform: with Applications to Basis Construction, Regression, and Subspace Approximation in L1
CoRR, 2012

Rich Coresets For Constrained Linear Regression
CoRR, 2012

2011
Spectral counting of triangles via element-wise sparsification and triangle-based link recommendation.
Soc. Netw. Anal. Min., 2011

Connectivity in time-graphs.
Pervasive Mob. Comput., 2011

Faster least squares approximation.
Numerische Mathematik, 2011

A note on element-wise matrix sparsification via a matrix-valued Bernstein inequality.
Inf. Process. Lett., 2011

Improving Analog and RF Device Yield through Performance Calibration.
IEEE Des. Test Comput., 2011

Stochastic Dimensionality Reduction for K-means Clustering
CoRR, 2011

Sparse Features for PCA-Like Linear Regression.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

On proving the efficiency of alternative RF tests.
Proceedings of the 2011 IEEE/ACM International Conference on Computer-Aided Design, 2011

2010
RF Specification Test Compaction Using Learning Machines.
IEEE Trans. Very Large Scale Integr. Syst., 2010

A Note on Element-wise Matrix Sparsification via Matrix-valued Chernoff Bounds
CoRR, 2010

Tensor sparsification via a bound on the spectral norm of random tensors
CoRR, 2010

Effective Resistances, Statistical Leverage, and Applications to Linear Equation Solving
CoRR, 2010

Random Projections for $k$-means Clustering.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Random walks in time-graphs.
Proceedings of the Second International Workshop on Mobile Opportunistic Networking, 2010

Post-production performance calibration in analog/RF devices.
Proceedings of the 2011 IEEE International Test Conference, 2010

2009
Sampling Algorithms and Coresets for $\ell<sub>p</sub> Regression. SIAM J. Comput., 2009 CUR matrix decompositions for improved data analysis. Proc. Natl. Acad. Sci. USA, 2009 On Boosting the Accuracy of Non-RF to RF Correlation-Based Specification Test Compaction. J. Electron. Test., 2009 An improved approximation algorithm for the column subset selection problem. Proceedings of the Twentieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2009 Unsupervised Feature Selection for the$k\$-means Clustering Problem.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Spectral Counting of Triangles in Power-Law Networks via Element-Wise Sparsification.
Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining, 2009

2008
Tensor-CUR Decompositions for Tensor-Based Data.
SIAM J. Matrix Anal. Appl., 2008

Relative-Error CUR Matrix Decompositions.
SIAM J. Matrix Anal. Appl., 2008

Sampling subproblems of heterogeneous Max-Cut problems and approximation algorithms.
Random Struct. Algorithms, 2008

Random Projections for the Nonnegative Least-Squares Problem
CoRR, 2008

Sampling algorithms and coresets for ℓ<sub><i>p</i></sub> regression.
Proceedings of the Nineteenth Annual ACM-SIAM Symposium on Discrete Algorithms, 2008

Unsupervised feature selection for principal components analysis.
Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008

Confidence Estimation in Non-RF to RF Correlation-Based Specification Test Compaction.
Proceedings of the 13th European Test Symposium, 2008

2007
Sampling Algorithms and Coresets for Lp Regression
CoRR, 2007

Non-RF to RF Test Correlation Using Learning Machines: A Case Study.
Proceedings of the 25th IEEE VLSI Test Symposium (VTS 2007), 2007

Feature selection methods for text classification.
Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007

2006
Entropy-driven parity-tree selection for low-overhead concurrent error detection in finite state machines.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2006

Fast Monte Carlo Algorithms for Matrices III: Computing a Compressed Approximate Matrix Decomposition.
SIAM J. Comput., 2006

Fast Monte Carlo Algorithms for Matrices II: Computing a Low-Rank Approximation to a Matrix.
SIAM J. Comput., 2006

Fast Monte Carlo Algorithms for Matrices I: Approximating Matrix Multiplication.
SIAM J. Comput., 2006

Randomized Algorithms for Matrices and Massive Data Sets.
Proceedings of the 32nd International Conference on Very Large Data Bases, 2006

Sampling algorithms for <i>l</i><sub>2</sub> regression and applications.
Proceedings of the Seventeenth Annual ACM-SIAM Symposium on Discrete Algorithms, 2006

Distance Matrix Reconstruction from Incomplete Distance Information for Sensor Network Localization.
Proceedings of the Third Annual IEEE Communications Society Conference on Sensor, 2006

Subspace Sampling and Relative-Error Matrix Approximation: Column-Row-Based Methods.
Proceedings of the Algorithms, 2006

Subspace Sampling and Relative-Error Matrix Approximation: Column-Based Methods.
Proceedings of the Approximation, 2006

2005
Compaction-based concurrent error detection for digital circuits.
Microelectron. J., 2005

On the Nyström Method for Approximating a Gram Matrix for Improved Kernel-Based Learning.
J. Mach. Learn. Res., 2005

Sampling Sub-problems of Heterogeneous Max-cut Problems and Approximation Algorithms.
Proceedings of the STACS 2005, 2005

Energy Minimization via Graph Cuts: Settling What is Possible.
Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), 2005

Approximating a Gram Matrix for Improved Kernel-Based Learning.
Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005

2004
Fast Universalization of Investment Strategies.
SIAM J. Comput., 2004

Clustering Large Graphs via the Singular Value Decomposition.
Mach. Learn., 2004

Cost-Driven Selection of Parity Trees.
Proceedings of the 22nd IEEE VLSI Test Symposium (VTS 2004), 2004

Concurrent Error Detection for Combinational and Sequential Logic via Output Compaction.
Proceedings of the 5th International Symposium on Quality of Electronic Design (ISQED 2004), 2004

Studying E-Mail Graphs for Intelligence Monitoring and Analysis in the Absence of Semantic Information.
Proceedings of the Intelligence and Security Informatics, 2004

On Concurrent Error Detection with Bounded Latency in FSMs.
Proceedings of the 2004 Design, 2004

2003
SPaRe: selective partial replication for concurrent fault-detection in FSMs.
IEEE Trans. Instrum. Meas., 2003

Pass efficient algorithms for approximating large matrices.
Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete Algorithms, 2003

Concurrent Fault Detection in Random Combinational Logic.
Proceedings of the 4th International Symposium on Quality of Electronic Design (ISQED 2003), 2003

On Compaction-Based Concurrent Error Detection.
Proceedings of the 9th IEEE International On-Line Testing Symposium (IOLTS 2003), 2003

Independent Test Sequence Compaction through Integer Programming.
Proceedings of the 21st International Conference on Computer Design (ICCD 2003), 2003

Non-Intrusive Concurrent Error Detection in FSMs through State/Output Compaction and Monitoring via Parity Trees.
Proceedings of the 2003 Design, 2003

2002
Competitive recommendation systems.
Proceedings of the Proceedings on 34th Annual ACM Symposium on Theory of Computing, 2002

Fast Universalization of Investment Strategies with Provably Good Relative Returns.
Proceedings of the Automata, Languages and Programming, 29th International Colloquium, 2002

Non-Intrusive Design of Concurrently Self-Testable FSMs.
Proceedings of the 11th Asian Test Symposium (ATS 2002), 18-20 November 2002, Guam, USA, 2002

2001
An Experimental Evaluation of a Monte-Carlo Algorithm for Singular Value Decomposition.
Proceedings of the Advances in Informatics, 8th Panhellenic Conference on Informatics, 2001

Fast Monte-Carlo Algorithms for Approximate Matrix Multiplication.
Proceedings of the 42nd Annual Symposium on Foundations of Computer Science, 2001

1999
Clustering in Large Graphs and Matrices.
Proceedings of the Tenth Annual ACM-SIAM Symposium on Discrete Algorithms, 1999