Ameet Talwalkar

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Virginia SmithCarnegie Mellon UniversityVerified email at cmu.edu
Liam LiCarnegie Mellon UniversityVerified email at liamcli.com
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Mikhail KhodakCMUVerified email at cs.princeton.edu
Tian LiUniversity of ChicagoVerified email at uchicago.edu
Kevin JamiesonAssociate Professor, University of WashingtonVerified email at cs.washington.edu
Mehryar MohriHead, ML Theory, Google Research; Professor, Courant Institute of Mathematical Sciences.Verified email at google.com
Anit Kumar SahuAmazonVerified email at amazon.com
Maria-Florina BalcanProfessor, School of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Michael FranklinUniversity of ChicagoVerified email at uchicago.edu
Maziar SanjabiMeta AIVerified email at fb.com
Gregory PlumbCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Valerie ChenCarnegie Mellon UniversityVerified email at cmu.edu
Sanjiv KumarGoogle Fellow, VP, Google ResearchVerified email at google.com
Giulia DeSalvoGoogle ResearchVerified email at GOOGLE.COM
Matei ZahariaUC Berkeley and DatabricksVerified email at berkeley.edu
Manzil ZaheerGoogle ResearchVerified email at cmu.edu
Sebastian CaldasGoogleVerified email at google.com
Lester MackeyMicrosoft ResearchVerified email at microsoft.com
Tim KraskaMITVerified email at mit.edu

Ameet Talwalkar

CMU, Datadog

Verified email at cmu.edu - Homepage

Machine Learning


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Federated optimization in heterogeneous networks T Li, AK Sahu, M Zaheer, M Sanjabi, A Talwalkar, V Smith Proceedings of Machine learning and systems 2, 429-450, 2020	6552	2020
Federated learning: Challenges, methods, and future directions T Li, AK Sahu, A Talwalkar, V Smith IEEE signal processing magazine 37 (3), 50-60, 2020	6034	2020
Hyperband: A novel bandit-based approach to hyperparameter optimization L Li, K Jamieson, G DeSalvo, A Rostamizadeh, A Talwalkar arXiv preprint arXiv:1603.06560, 2016	3244	2016
Mllib: Machine learning in apache spark X Meng, J Bradley, B Yavuz, E Sparks, S Venkataraman, D Liu, ... Journal of Machine Learning Research 17 (34), 1-7, 2016	2494	2016
Federated multi-task learning V Smith, CK Chiang, M Sanjabi, AS Talwalkar Advances in neural information processing systems 30, 2017	2354	2017
Leaf: A benchmark for federated settings S Caldas, SMK Duddu, P Wu, T Li, J Konečný, HB McMahan, V Smith, ... arXiv preprint arXiv:1812.01097, 2018	1634	2018
A large-scale evaluation of computational protein function prediction P Radivojac, WT Clark, TR Oron, AM Schnoes, T Wittkop, A Sokolov, ... Nature methods 10 (3), 221-227, 2013	1152	2013
Random search and reproducibility for neural architecture search L Li, A Talwalkar Uncertainty in artificial intelligence, 367-377, 2020	879	2020
Non-stochastic best arm identification and hyperparameter optimization K Jamieson, A Talwalkar Artificial intelligence and statistics, 240-248, 2016	800	2016
Expanding the reach of federated learning by reducing client resource requirements S Caldas, J Konečny, HB McMahan, A Talwalkar arXiv preprint arXiv:1812.07210, 2018	545	2018
A scalable bootstrap for massive data A Kleiner, A Talwalkar, P Sarkar, MI Jordan Journal of the Royal Statistical Society, Series B, 2013	528	2013
A system for massively parallel hyperparameter tuning L Li, K Jamieson, A Rostamizadeh, E Gonina, J Ben-Tzur, M Hardt, ... Proceedings of machine learning and systems 2, 230-246, 2020	490	2020
MLbase: A Distributed Machine-learning System. T Kraska, A Talwalkar, JC Duchi, R Griffith, MJ Franklin, MI Jordan Cidr 1, 2-1, 2013	487	2013
Sampling methods for the Nyström method S Kumar, M Mohri, A Talwalkar The Journal of Machine Learning Research 13 (1), 981-1006, 2012	478	2012
A field guide to federated optimization J Wang, Z Charles, Z Xu, G Joshi, HB McMahan, M Al-Shedivat, G Andrew, ... arXiv preprint arXiv:2107.06917, 2021	428	2021
Adaptive gradient-based meta-learning methods M Khodak, MFF Balcan, AS Talwalkar Advances in Neural Information Processing Systems 32, 2019	424	2019
Gradient descent on neural networks typically occurs at the edge of stability JM Cohen, S Kaur, Y Li, JZ Kolter, A Talwalkar arXiv preprint arXiv:2103.00065, 2021	293	2021
Large-scale manifold learning A Talwalkar, S Kumar, H Rowley 2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2008	278	2008
Model agnostic supervised local explanations G Plumb, D Molitor, AS Talwalkar Advances in neural information processing systems 31, 2018	274	2018
One-shot federated learning N Guha, A Talwalkar, V Smith arXiv preprint arXiv:1902.11175, 2019	271	2019

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