Dimitris Papailiopoulos

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Alexandros G DimakisProfessor, ECE University of Texas at AustinVerified email at austin.utexas.edu
Hongyi WangCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Kannan RamchandranProfessor of Electrical Engineering and Computer Science, UC BerkeleyVerified email at eecs.berkeley.edu
Kangwook LeeUniversity of Wisconsin-MadisonVerified email at wisc.edu
Zachary CharlesResearch Scientist, GoogleVerified email at google.com
Megasthenis AsterisUniversity of Texas at AustinVerified email at utexas.edu
Shashank RajputGraduate Student, University of Wisconsin - MadisonVerified email at wisc.edu
Maximilian LamHarvard UniversityVerified email at g.harvard.edu
Xinghao PanSenior Research Scientist @ DSO National LaboratoriesVerified email at dso.org.sg
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Ramtin PedarsaniAssociate Professor, Electrical and Computer Engineering, UC Santa BarbaraVerified email at ece.ucsb.edu
George KarystinosTechnical University of CreteVerified email at telecom.tuc.gr
Jy-yong SohnUniversity of Wisconsin-MadisonVerified email at wisc.edu
Benjamin RechtAssociate Professor of EECS, University of California, BerkeleyVerified email at eecs.berkeley.edu
Kartik SreenivasanGraduate Student, University of Wisconsin-MadisonVerified email at wisc.edu
Saurabh AgarwalUW-MadisonVerified email at wisc.edu
Ankit Singh RawatResearch Scientist, GoogleVerified email at google.com
Scott Chun-Yang ChenFacebook, CaltechVerified email at fb.com
Maheswaran (Mahesh) SathiamoorthyGoogle ResearchVerified email at google.com
Dhruba BorthakurHDFS, RocksDB, RocksetVerified email at rockset.com

Dimitris Papailiopoulos

Assistant Professor, University of Wisconsin-Madison

Verified email at papail.io - Homepage

Machine Learning Information Theory Optimization


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XORing elephants: Novel erasure codes for big data M Sathiamoorthy, M Asteris, D Papailiopoulos, AG Dimakis, R Vadali, ... Proceedings of the VLDB Endowment 6 (5), 325-336, 2013	835	2013
Speeding up distributed machine learning using codes K Lee, M Lam, R Pedarsani, D Papailiopoulos, K Ramchandran IEEE Transactions on Information Theory, 2017	700	2017
Locally repairable codes DS Papailiopoulos, AG Dimakis IEEE Transactions on Information Theory 60 (10), 5843-5855, 2014	526	2014
Federated Learning with Matched Averaging H Wang, M Yurochkin, Y Sun, D Papailiopoulos, Y Khazaeni ICLR 2020, 2020	338	2020
Locality and availability in distributed storage AS Rawat, DS Papailiopoulos, AG Dimakis, S Vishwanath IEEE Transactions on Information Theory 62 (8), 4481-4493, 2016	241	2016
Simple regenerating codes: Network coding for cloud storage DS Papailiopoulos, J Luo, AG Dimakis, C Huang, J Li 2012 Proceedings IEEE INFOCOM, 2801-2805, 2012	239	2012
Atomo: Communication-efficient learning via atomic sparsification H Wang, S Sievert, S Liu, Z Charles, S Wright, D Papailiopoulos Advances in Neural Information Processing Systems 31, 9850-9861, 2018	233	2018
Optimal locally repairable codes and connections to matroid theory I Tamo, DS Papailiopoulos, AG Dimakis IEEE Transactions on Information Theory 62 (12), 6661-6671, 2016	214	2016
Interference alignment as a rank constrained rank minimization DS Papailiopoulos, AG Dimakis IEEE Transactions on Signal Processing 60 (8), 4278-4288, 2012	203	2012
DRACO: Byzantine-resilient Distributed Training via Redundant Gradients L Chen, H Wang, Z Charles, D Papailiopoulos International Conference on Machine Learning, 902-911, 2018	196*	2018
Repair optimal erasure codes through hadamard designs DS Papailiopoulos, AG Dimakis, VR Cadambe IEEE transactions on information theory 59 (5), 3021-3037, 2013	195	2013
Perturbed Iterate Analysis for Asynchronous Stochastic Optimization H Mania, X Pan, D Papailiopoulos, B Recht, K Ramchandran, MI Jordan SIAM Journal on Optimization 27 (4), 2202-2229, 2017	188	2017
Attack of the tails: Yes, you really can backdoor federated learning H Wang, K Sreenivasan, S Rajput, H Vishwakarma, S Agarwal, J Sohn, ... Advances in Neural Information Processing Systems 33, 2020	134	2020
Gradient Diversity: a Key Ingredient for Scalable Distributed Learning D Yin, A Pananjady, M Lam, D Papailiopoulos, K Ramchandran, P Bartlett Proceedings of the 21th International Conference on Artificial Intelligence …, 2018	109*	2018
Parallel Correlation Clustering on Big Graphs X Pan, D Papailiopoulos, S Oymak, B Recht, K Ramchandran, MI Jordan Advances in Neural Information Processing Systems, 82-90, 2015	90	2015
Stability and generalization of learning algorithms that converge to global optima Z Charles, D Papailiopoulos International Conference on Machine Learning, 745-754, 2018	87	2018
Provable Deterministic Leverage Score Sampling D Papailiopoulos, A Kyrillidis, C Boutsidis arXiv preprint arXiv:1404.1530, 2014	75	2014
Sparse PCA through low-rank approximations D Papailiopoulos, A Dimakis, S Korokythakis International Conference on Machine Learning, 747-755, 2013	74	2013
DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation S Rajput, H Wang, Z Charles, D Papailiopoulos Advances in Neural Information Processing Systems, 10320-10330, 2019	69	2019
Approximate Gradient Coding via Sparse Random Graphs Z Charles, D Papailiopoulos, J Ellenberg arXiv preprint arXiv:1711.06771, 2017	65	2017

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