# Christos Boutsidis

According to our database

Collaborative distances:

^{1}, Christos Boutsidis authored at least 25 papers between 2008 and 2016.Collaborative distances:

## Timeline

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## Bibliography

2016

Optimal principal component analysis in distributed and streaming models.

Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing, 2016

Optimal Sparse Linear Encoders and Sparse PCA.

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Randomized Dimensionality Reduction for k-Means Clustering.

IEEE Trans. Information Theory, 2015

Online Principal Components Analysis.

Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, 2015

Spectral Clustering via the Power Method - Provably.

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Random Projections for Linear Support Vector Machines.

TKDD, 2014

A note on sparse least-squares regression.

Inf. Process. Lett., 2014

Optimal CUR matrix decompositions.

Proceedings of the Symposium on Theory of Computing, 2014

Provable deterministic leverage score sampling.

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Faster SVD-truncated regularized least-squares.

Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

2013

Deterministic Feature Selection for $k$-Means Clustering.

IEEE Trans. Information Theory, 2013

Near-Optimal Coresets for Least-Squares Regression.

IEEE Trans. Information Theory, 2013

Improved Matrix Algorithms via the Subsampled Randomized Hadamard Transform.

SIAM J. Matrix Analysis Applications, 2013

Faster Subset Selection for Matrices and Applications.

SIAM J. Matrix Analysis Applications, 2013

Efficient Dimensionality Reduction for Canonical Correlation Analysis.

Proceedings of the 30th International Conference on Machine Learning, 2013

Equity factor analysis via column subset selection.

Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013

Random Projections for Support Vector Machines.

Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

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

Near Optimal Column-Based Matrix Reconstruction.

Proceedings of the IEEE 52nd Annual Symposium on Foundations of Computer Science, 2011

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

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

2008

SVD based initialization: A head start for nonnegative matrix factorization.

Pattern Recognition, 2008

Unsupervised feature selection for principal components analysis.

Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008

Clustered subset selection and its applications on it service metrics.

Proceedings of the 17th ACM Conference on Information and Knowledge Management, 2008