About me

I am a postdoctoral fellow and co-PI at University of California Berkeley (UCB) in the Department of Statistics and ICSI. I am working with Michael Mahoney. Before that I completed a PhD in optimization at University of Edinburgh (UoE) under the supervision of Prof. Jacek Gondzio.

My work focuses on large scale optimization, higher order methods and communication avoiding methods. Generally, anything related to numerical methods in optimization. Another line of work that I am interested in is local graph clustering applications and methods as well as statistical models and methods for computational social science.

Publications

Submitted conference papers

D. Zhang, K. Fountoulakis, J. Cao, M. Yin, M. Mahoney and A. Pozdnoukhov. Social Discrete Choice Models. arXiv:1703.07520.
(Download pdf)

Submitted journal papers

K. Fountoulakis, F. Roosta-Khorasani, J. Shun, X. Cheng and M. Mahoney. Variational Perspective on Local Graph Clustering. arXiv:1602.01886.
(Download pdf)

K. Fountoulakis and R. Tappenden. A Flexible Coordinate Descent Method. arXiv:1507.03713.
(Download pdf, Download software)

Published journal papers

K. Fountoulakis, A. Kundu, E.-M. Kontopoulou and P. Drineas. A Randomized Rounding Algorithm for Sparse PCA. arXiv:1508.03337. (accepted to ACM Transactions on Knowledge Discovery from Data)
(Download pdf)

K. Fountoulakis, D. Gleich and M. Mahoney. An optimization approach to locally-biased graph algorithms. arXiv:1607.04940 (to appear at Proceedings of the IEEE).
(Download pdf)

J. Shun, F. Roosta-Khorasani, K. Fountoulakis and M. Mahoney. Parallel Local Graph Clustering (accepted to VLDB 2016).
(Download pdf)

K. Fountoulakis and J. Gondzio. Performance of First- and Second-Order Methods for Big Data Optimization. Technical Report ERGO-15-005. (accepted to Computational Optimization and Applications)
(Download pdf, Download software)

I. Dassios, K. Fountoulakis and J. Gondzio. A Preconditioner for a Primal-dual Newton Conjugate Gradients Method for Compressed Sensing Problems. Technical Report ERGO-14-021.(accepted to SIAM Journal on Scientific Computing)
(Download pdf, Download software)

K. Fountoulakis and J. Gondzio. A Second-Order Method for Strongly-Convex L1-Regularization Problems. Math. Prog. A (accepted), 2015.
(Download pdf, Download software)

K. Fountoulakis, J. Gondzio, and P. Zhlobich. Matrix-free interior point method for compressed sensing problems. Math. Prog. Comp., 6 (1): 1-31, 2014.
(Download pdf, Download software)

Technical reports

A. Devarakonda, K. Fountoulakis, J. Demmel and M. Mahoney. Avoiding communication in primal and dual block coordinate descent methods. arXiv:1612.04003.
(Download pdf)

PhD Thesis

Higher-Order Methods for Large-Scale Optimization
(Download pdf)

Software

Trillion (Download Trillion)

Instance generators for l1-regularized over- and underdetermined least squares. The generators are implemented in MATLAB, they are memoryless and computationally inexpensive. Hence, large-scale instances can be created.

pdNCG: primal-dual Newton Conjugate Gradients (Download pdNCG)

A MATLAB implementation for the solution of unconstrained l1-regularized problems. For example, Machine Learning problems, such as l1-regularized least-squares and logistic regression, Compressed Sensing problems, such as l1-synthesis, l1-analysis and isotropic total-variation. The solver is memoryless, it requires only matrix-vector product operations, hence it is appropriate for large-scale instances.

MFIPMCS: Matrix-free Interior Point Method for Compressed Sensing (Download MFIPMCS)

An interior point method implemented in MATLAB for the solution of real valued compressed sensing problems. The "matrix-free" implies that only matrix-vector products operations are allowed and the process is memoryless. The solver implements efficient preconditioning techniques for the fast solution of linear systems at every iteration.

FCD: Flexible Coordinate Descent (Dowload MATLAB scripts.)

This software only reproduces the experiments in paper "Flexible Coordinate Descent".

Coupling Optimization and Local Graph Clustering (Dowload MATLAB scripts.)

Strongly local proximal block coordinate and full gradient descent methods for graph clustering (only for experimentation).

Contact

Address: 1947 Center Street, Ste. 600, Berkeley, CA 94704

Email:

Talks

Workshop on Algorithms for Modern Massive Data Sets 2016 (Local graph clustering algorithms: an optimization perspective)
(Download pdf, Video)

International Symposium on Mathematical Programming (ISMP2015) (Performance of First- and Second-Order Methods for Large-Scale Optimization)
(Download pdf

Oxford Numerical Analysis Group Internal Seminar (On Newton-type methods for support vector machines and signal reconstruction problems)
(Download pdf)

SIAM Conferecne on Computational Science and Engineering (On primal-dual Newton conjugate gradients for compressed sensing)
(Download pdf)

ERGO Seminar (On robust block coordinate descent and primal-dual Newton conjugate gradients)
(Download pdf)

IMA Conference on the Mathematical Challenges of Big Data 2014 (On robust block coordinate descent)
(Download pdf)

Edinburgh SIAM Student Chapter Conference 2014 (On robust block coordinate descent)
(Download pdf)

4th IMA Conference on Numerical Linear Algebra and Optimisation (On primal-dual Newton conjugate gradients for l1-regularized problems)
(Download pdf)

SIAM Conference on Optimization 2014 (On primal-dual Newton conjugate gradients for sparse signal reconstruction)
(Download pdf)

12th EUROPT Workshop on Advances in Continuous Optimization 2014 (On primal-dual Newton conjugate gradients for l1-regularized problems)
(Download pdf)

20th Conference of the International Federation of Operational Research Societies (IFORS) 2014 (On primal-dual Newton conjugate gradients for sparse signal reconstruction)
(Download pdf)

Computational linear algebra and optimization for the Digital Economy workshop 2013 (On second-order methods for various l1-regularized problems)
(Download pdf)

International Conference on Continuous Optimization (ICCOPT) 2013 (On second-order methods with continuation for various l1-regularized problems)
(Download pdf)

11th EUROPT Workshop on Advances in Continuous Optimization (On second-order methods with continuation for l1-regularized problems in Machine Learning)
(Download pdf)

European Conference on Operational Research EURO/INFORMS 2013 (On second-order methods with continuation for l1-regularized problems in Machine Learning)
(Download pdf)

International Conference on Preconditioning Techniques for Scientific and Industrial Applications 2013 (On preconditioners for second-order methods applied to l1-regularized problems)
(Download pdf)

Cambdridge Mathematical Socienty Research in the UK afternnon 2012 (Brief introduction to interior point methods)
(Download pdf)

Conference 3rd IMA Conference on Numerical Linear Algebra and Optimization (NLAO) (On interior point methods for sparse signal reconstruction)
(Download pdf)

Operational Research 54 (OR54) (On interior point methods for sparse signal reconstruction)
(Download pdf)

International Symposium on Mathematical Programming (ISMP2012) (On interior point methods for sparse signal reconstruction)
(Download pdf)

3rd Conference on Optimization Methods and Software (OMS) (On interior point methods for sparse signal reconstruction)
(Download pdf)