Kimon Fountoulakis

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Michael MahoneyProfessor of Statistics, UC BerkeleyVerified email at stat.berkeley.edu
Jacek GondzioProfessor of Optimization, School of Mathematics, Edinburgh UniversityVerified email at ed.ac.uk
Shenghao YangDavid R. Cheriton School of Computer Science, University of WaterlooVerified email at uwaterloo.ca
Aseem BaranwalUniversity of WaterlooVerified email at uwaterloo.ca
Julian ShunMITVerified email at mit.edu
Fred RoostaUniversity of QueenslandVerified email at uq.edu.au
David GleichPurdue UniversityVerified email at purdue.edu
Di WangGoogle ResearchVerified email at eecs.berkeley.edu
Ioannis DassiosUniversity College DublinVerified email at ucd.ie
James W DEMMELProfessor of EECS and Mathematics, UC BerkeleyVerified email at berkeley.edu
Rachael TappendenUniversity of CanterburyVerified email at canterbury.ac.nz
Xiang ChengMassachusetts Institute of TechnologyVerified email at berkeley.edu
Artur Back de LucaDavid R. Cheriton School of Computer Science, University of WaterlooVerified email at uwaterloo.ca
Aditya DevarakondaWake Forest UniversityVerified email at wfu.edu
Monika HenzingerProfessor of Computer Science, Institute of Science and Technology Austria (ISTA)Verified email at ist.ac.at
Satish B RaoVerified email at berkeley.edu
Petros DrineasProfessor, Computer Science Department, Purdue UniversityVerified email at purdue.edu
Abhisek KunduResearch Scientist, Intel Parallel Computing Labs, IndiaVerified email at intel.com
Felix BoruttaLudwig-Maximilians-Universität MünchenVerified email at dbs.ifi.lmu.de
Evgeniy FaermanPhD Student, Ludwig-Maximilians-Universität MünchenVerified email at dbs.ifi.lmu.de

Kimon Fountoulakis

David R. Cheriton School of Computer Science, University of Waterloo

Verified email at uwaterloo.ca - Homepage

Machine Learning on Graphs Machine Learning for Algorithmic Reasoning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
A second-order method for strongly convex -regularization problems K Fountoulakis, J Gondzio Mathematical Programming 156 (1), 189-219, 2016	95	2016
Matrix-free interior point method for compressed sensing problems K Fountoulakis, J Gondzio, P Zhlobich Mathematical Programming Computation 6, 1-31, 2014	90	2014
Parallel local graph clustering J Shun, F Roosta-Khorasani, K Fountoulakis, MW Mahoney arXiv preprint arXiv:1604.07515, 2016	89	2016
A preconditioner for a primal-dual newton conjugate gradient method for compressed sensing problems I Dassios, K Fountoulakis, J Gondzio SIAM Journal on Scientific Computing 37 (6), A2783-A2812, 2015	85*	2015
Graph convolution for semi-supervised classification: Improved linear separability and out-of-distribution generalization A Baranwal, K Fountoulakis, A Jagannath arXiv preprint arXiv:2102.06966, 2021	77	2021
Variational Perspective on Local Graph Clustering K Fountoulakis, F Roosta-Khorasani, J Shun, X Cheng, MW Mahoney arXiv preprint arXiv:1602.01886, 2018	54*	2018
Capacity releasing diffusion for speed and locality D Wang, K Fountoulakis, M Henzinger, MW Mahoney, S Rao International Conference on Machine Learning, 3598-3607, 2017	45	2017
A flexible coordinate descent method K Fountoulakis, R Tappenden Computational Optimization and Applications 70 (2), 351-394, 2018	39*	2018
Performance of first-and second-order methods for\ ell _1-regularized least squares problems K Fountoulakis, J Gondzio Computational Optimization and Applications 65 (3), 605-635, 2016	35*	2016
Graph attention retrospective K Fountoulakis, A Levi, S Yang, A Baranwal, A Jagannath arXiv preprint arXiv:2202.13060, 2022	34	2022
Effects of graph convolutions in multi-layer networks A Baranwal, K Fountoulakis, A Jagannath arXiv preprint arXiv:2204.09297, 2022	31	2022
Lasagne: Locality and structure aware graph node embedding E Faerman, F Borutta, K Fountoulakis, MW Mahoney 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI), 246-253, 2018	27	2018
An optimization approach to locally-biased graph algorithms K Fountoulakis, DF Gleich, MW Mahoney Proceedings of the IEEE 105 (2), 256-272, 2017	22	2017
Flow-based algorithms for improving clusters: A unifying framework, software, and performance K Fountoulakis, M Liu, DF Gleich, MW Mahoney SIAM Review 65 (1), 59-143, 2023	20	2023
Local hyper-flow diffusion K Fountoulakis, P Li, S Yang Advances in neural information processing systems 34, 27683-27694, 2021	19	2021
Avoiding communication in primal and dual block coordinate descent methods A Devarakonda, K Fountoulakis, J Demmel, MW Mahoney SIAM Journal on Scientific Computing 41 (1), C1-C27, 2019	18	2019
p-Norm Flow Diffusion for Local Graph Clustering K Fountoulakis, D Wang, S Yang International Conference on Machine Learning, 3222-3232, 2020	17	2020
A short introduction to local graph clustering methods and software K Fountoulakis, DF Gleich, MW Mahoney arXiv preprint arXiv:1810.07324, 2018	14	2018
Targeted pandemic containment through identifying local contact network bottlenecks S Yang, P Senapati, D Wang, CT Bauch, K Fountoulakis PLoS computational biology 17 (8), e1009351, 2021	11	2021
Statistical guarantees for local graph clustering W Ha, K Fountoulakis, MW Mahoney Journal of Machine Learning Research 22 (148), 1-54, 2021	11	2021

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