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 WangIncoming Assistant Professor, Rutgers UniversityVerified email at andrew.cmu.edu
Shashank RajputResearch Scientist, MosaicML (Databricks)Verified email at databricks.com
Zachary CharlesResearch Scientist, GoogleVerified email at google.com
Kannan RamchandranProfessor of Electrical Engineering and Computer Science, UC BerkeleyVerified email at eecs.berkeley.edu
Jy-yong SohnYonsei UniversityVerified email at yonsei.ac.kr
Kartik SreenivasanGraduate Student, University of Wisconsin-MadisonVerified email at wisc.edu
Megasthenis AsterisUniversity of Texas at AustinVerified email at utexas.edu
Ramtin PedarsaniAssociate Professor, Electrical and Computer Engineering, UC Santa BarbaraVerified email at ece.ucsb.edu
Samet OymakUniversity of MichiganVerified email at umich.edu
George KarystinosTechnical University of CreteVerified email at telecom.tuc.gr
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
Lingjiao ChenStanford UniversityVerified email at stanford.edu
Harit VishwakarmaCS PhD Candidate, University of Wisconsin MadisonVerified email at cs.wisc.edu
Benjamin RechtProfessor of EECS, University of California, BerkeleyVerified email at eecs.berkeley.edu
Angeliki GiannouUniversity of Wisconsin–MadisonVerified email at wisc.edu
Yuekai SunUniversity of MichiganVerified email at umich.edu
Yasaman KhazaeniCapitalOne, Wayfair, IBM, Boston UniversityVerified email at bu.edu

Dimitris Papailiopoulos

Researcher at Microsoft Research & Assoc. Professor at University of Wisconsin

Verified email at papail.io - Homepage

Machine Learning Information Theory Optimization


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Federated Learning with Matched Averaging H Wang, M Yurochkin, Y Sun, D Papailiopoulos, Y Khazaeni ICLR 2020, 2020	1206	2020
Speeding up distributed machine learning using codes K Lee, M Lam, R Pedarsani, D Papailiopoulos, K Ramchandran IEEE Transactions on Information Theory, 2017	962	2017
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	926	2013
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	600	2020
Locally repairable codes DS Papailiopoulos, AG Dimakis IEEE Transactions on Information Theory 60 (10), 5843-5855, 2014	598	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	393	2018
DRACO: Byzantine-resilient Distributed Training via Redundant Gradients L Chen, H Wang, Z Charles, D Papailiopoulos International Conference on Machine Learning, 902-911, 2018	294*	2018
Locality and availability in distributed storage AS Rawat, DS Papailiopoulos, AG Dimakis, S Vishwanath IEEE Transactions on Information Theory 62 (8), 4481-4493, 2016	286	2016
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	267	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	259	2017
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	250	2012
Repair optimal erasure codes through hadamard designs DS Papailiopoulos, AG Dimakis, VR Cadambe IEEE transactions on information theory 59 (5), 3021-3037, 2013	231	2013
Interference alignment as a rank constrained rank minimization DS Papailiopoulos, AG Dimakis IEEE Transactions on Signal Processing 60 (8), 4278-4288, 2012	218	2012
Stability and generalization of learning algorithms that converge to global optima Z Charles, D Papailiopoulos International Conference on Machine Learning, 745-754, 2018	168	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	158	2018
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	129	2019
Transformers as Algorithms: Generalization and Stability in In-context Learning Y Li, ME Ildiz, D Papailiopoulos, S Oymak ICML 2023, 2023	124*	2023
Optimal Lottery Tickets via Subset Sum: Logarithmic Over-Parameterization is Sufficient A Pensia, S Rajput, A Nagle, H Vishwakarma, D Papailiopoulos Advances in Neural Information Processing Systems 33, 2020	106	2020
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	106	2015
Provable Deterministic Leverage Score Sampling D Papailiopoulos, A Kyrillidis, C Boutsidis arXiv preprint arXiv:1404.1530, 2014	101	2014

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