Ameet Talwalkar

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Mehryar MohriHead, Learning Theory Team, Google Research; Professor, Courant Institute of Mathematical SciencesVerified email at google.com
Afshin RostamizadehGoogle ResearchVerified email at google.com
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Liam LiCarnegie Mellon UniversityVerified email at liamcli.com
Tian LiCarnegie Mellon UniversityVerified email at cmu.edu
Kevin JamiesonAssistant Professor, University of WashingtonVerified email at cs.washington.edu
Michael FranklinLiew Family Chair of Computer Science, University of ChicagoVerified email at uchicago.edu
Mikhail KhodakCMUVerified email at cs.princeton.edu
Anit Kumar SahuAmazon Alexa AIVerified email at alumni.cmu.edu
Sanjiv KumarGoogle Fellow, VP, Google ResearchVerified email at google.com
Maziar SanjabiFacebook AIVerified email at fb.com
Matei ZahariaStanford DAWN Lab and DatabricksVerified email at cs.stanford.edu
Maria-Florina BalcanProfessor, School of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Lester MackeyMicrosoft ResearchVerified email at microsoft.com
Giulia DeSalvoNew York UniversityVerified email at GOOGLE.COM
Manzil ZaheerGoogle ResearchVerified email at cmu.edu
Gregory PlumbCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Sebastian CaldasPh.D. Student, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Xiangrui MengDatabricksVerified email at databricks.com
Purnamrita SarkarAssistant Professor, Statistics and Data Sciences, University of Texas at AustinVerified email at austin.utexas.edu

Ameet Talwalkar

CMU and Determined AI

Verified email at cmu.edu - Homepage

Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Foundations of Machine Learning M Mohri, A Rostamizadeh, A Talwalkar Cambridge, MA: MIT Press, 2018	4205	2018
Mllib: Machine learning in apache spark X Meng, J Bradley, B Yavuz, E Sparks, S Venkataraman, D Liu, ... The Journal of Machine Learning Research 17 (1), 1235-1241, 2016	2043	2016
Federated learning: Challenges, methods, and future directions T Li, AK Sahu, A Talwalkar, V Smith IEEE Signal Processing Magazine 37 (3), 50-60, 2020	1551	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	1367	2016
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	1205*	2020
Federated multi-task learning V Smith, CK Chiang, M Sanjabi, AS Talwalkar Advances in neural information processing systems 30, 2017	956	2017
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	872	2013
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	508	2018
Random search and reproducibility for neural architecture search L Li, A Talwalkar Uncertainty in artificial intelligence, 367-377, 2020	447	2020
MLbase: A Distributed Machine-learning System. T Kraska, A Talwalkar, JC Duchi, R Griffith, MJ Franklin, MI Jordan Cidr 1, 2-1, 2013	428	2013
A scalable bootstrap for massive data A Kleiner, A Talwalkar, P Sarkar, MI Jordan Journal of the Royal Statistical Society, Series B, 2013	397	2013
Non-stochastic best arm identification and hyperparameter optimization K Jamieson, A Talwalkar Artificial intelligence and statistics, 240-248, 2016	392	2016
Sampling methods for the Nyström method S Kumar, M Mohri, A Talwalkar The Journal of Machine Learning Research 13 (1), 981-1006, 2012	387	2012
Large-scale manifold learning A Talwalkar, S Kumar, H Rowley 2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2008	244	2008
Divide-and-Conquer Matrix Factorization LW Mackey, A Talwalkar, MI Jordan NIPS, 1134-1142, 2011	229	2011
MLI: An API for distributed machine learning ER Sparks, A Talwalkar, V Smith, J Kottalam, X Pan, J Gonzalez, ... 2013 IEEE 13th International Conference on Data Mining, 1187-1192, 2013	226	2013
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	209	2018
Joint link prediction and attribute inference using a social-attribute network NZ Gong, A Talwalkar, L Mackey, L Huang, ECR Shin, E Stefanov, ER Shi, ... ACM Transactions on Intelligent Systems and Technology (TIST) 5 (2), 27, 2014	201	2014
Knowing when you're wrong: building fast and reliable approximate query processing systems S Agarwal, H Milner, A Kleiner, A Talwalkar, M Jordan, S Madden, ... Proceedings of the 2014 ACM SIGMOD international conference on Management of …, 2014	197	2014
Adaptive gradient-based meta-learning methods M Khodak, MFF Balcan, AS Talwalkar Advances in Neural Information Processing Systems 32, 2019	185	2019

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