Dimitris Papailiopoulos

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Alexandros G DimakisProfessor, ECE University of Texas at AustinVerified email at austin.utexas.edu
Kangwook LeeUniversity of Wisconsin-MadisonVerified email at wisc.edu
Hongyi WangSenior Researcher, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
Kannan RamchandranProfessor of Electrical Engineering and Computer Science, UC BerkeleyVerified email at eecs.berkeley.edu
Zachary CharlesResearch Scientist, GoogleVerified email at google.com
Shashank RajputGraduate Student, University of Wisconsin - MadisonVerified email at wisc.edu
Megasthenis AsterisUniversity of Texas at AustinVerified email at utexas.edu
Jy-yong SohnYonsei UniversityVerified email at yonsei.ac.kr
Maximilian LamHarvard UniversityVerified email at g.harvard.edu
Kartik SreenivasanGraduate Student, University of Wisconsin-MadisonVerified email at wisc.edu
Ramtin PedarsaniAssociate Professor, Electrical and Computer Engineering, UC Santa BarbaraVerified email at ece.ucsb.edu
Xinghao PanVerified email at eecs.berkeley.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
George KarystinosTechnical University of CreteVerified email at telecom.tuc.gr
Benjamin RechtAssociate Professor of EECS, University of California, BerkeleyVerified email at eecs.berkeley.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
Shengchao LiuMila-UdeMVerified email at umontreal.ca

Dimitris Papailiopoulos

Associate 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	871	2013
Speeding up distributed machine learning using codes K Lee, M Lam, R Pedarsani, D Papailiopoulos, K Ramchandran IEEE Transactions on Information Theory, 2017	801	2017
Federated Learning with Matched Averaging H Wang, M Yurochkin, Y Sun, D Papailiopoulos, Y Khazaeni ICLR 2020, 2020	636	2020
Locally repairable codes DS Papailiopoulos, AG Dimakis IEEE Transactions on Information Theory 60 (10), 5843-5855, 2014	546	2014
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	300	2018
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	289	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	252	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	246	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	238*	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	232	2016
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	214	2017
Repair optimal erasure codes through hadamard designs DS Papailiopoulos, AG Dimakis, VR Cadambe IEEE transactions on information theory 59 (5), 3021-3037, 2013	206	2013
Interference alignment as a rank constrained rank minimization DS Papailiopoulos, AG Dimakis IEEE Transactions on Signal Processing 60 (8), 4278-4288, 2012	205	2012
Stability and generalization of learning algorithms that converge to global optima Z Charles, D Papailiopoulos International Conference on Machine Learning, 745-754, 2018	126	2018
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	125	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	98	2015
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	90	2019
Provable Deterministic Leverage Score Sampling D Papailiopoulos, A Kyrillidis, C Boutsidis arXiv preprint arXiv:1404.1530, 2014	87	2014
Sparse PCA through low-rank approximations D Papailiopoulos, A Dimakis, S Korokythakis International Conference on Machine Learning, 747-755, 2013	81	2013
Approximate Gradient Coding via Sparse Random Graphs Z Charles, D Papailiopoulos, J Ellenberg arXiv preprint arXiv:1711.06771, 2017	73	2017

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