Ameet Talwalkar

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Mehryar MohriHead, Learning Theory Team, Google Research; Professor, Courant Institute of Mathematical SciencesVerified email at google.com
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Afshin RostamizadehGoogle ResearchVerified email at google.com
Liam LiCarnegie Mellon UniversityVerified email at liamcli.com
Virginia SmithCarnegie 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
Sanjiv KumarDistinguished Scientist, GoogleVerified email at google.com
Lester MackeyMicrosoft ResearchVerified email at microsoft.com
Tian LiCarnegie Mellon UniversityVerified email at cmu.edu
Matei ZahariaStanford DAWN Lab and DatabricksVerified email at cs.stanford.edu
Tim KraskaMITVerified email at mit.edu
Giulia DeSalvoNew York UniversityVerified email at cims.nyu.edu
Anit Kumar SahuAmazon Alexa AIVerified email at alumni.cmu.edu
Maziar SanjabiFacebook AIVerified email at fb.com
Xiangrui MengDatabricksVerified email at databricks.com
Maria-Florina BalcanProfessor, School of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Purnamrita SarkarAssistant Professor, Statistics and Data Sciences, University of Texas at AustinVerified email at austin.utexas.edu
Reza Bosagh ZadehStanford and MatroidVerified email at stanford.edu
Shivaram VenkataramanUniversity of Wisconsin-MadisonVerified email at cs.wisc.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	2986	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	1696	2016
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	780	2013
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	721	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	505	2020
Federated multi-task learning V Smith, CK Chiang, M Sanjabi, A Talwalkar arXiv preprint arXiv:1705.10467, 2017	503	2017
MLbase: A Distributed Machine-learning System. T Kraska, A Talwalkar, JC Duchi, R Griffith, MJ Franklin, MI Jordan Cidr 1, 2-1, 2013	379	2013
A scalable bootstrap for massive data A Kleiner, A Talwalkar, P Sarkar, MI Jordan Journal of the Royal Statistical Society, Series B, 2013	341	2013
Sampling methods for the Nyström method S Kumar, M Mohri, A Talwalkar The Journal of Machine Learning Research 13 (1), 981-1006, 2012	339	2012
Federated optimization in heterogeneous networks T Li, AK Sahu, M Zaheer, M Sanjabi, A Talwalkar, V Smith arXiv preprint arXiv:1812.06127, 2018	325	2018
Random search and reproducibility for neural architecture search L Li, A Talwalkar Uncertainty in Artificial Intelligence, 367-377, 2020	256	2020
Large-scale manifold learning A Talwalkar, S Kumar, H Rowley 2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2008	226	2008
Non-stochastic best arm identification and hyperparameter optimization K Jamieson, A Talwalkar Artificial Intelligence and Statistics, 240-248, 2016	217	2016
Divide-and-Conquer Matrix Factorization LW Mackey, A Talwalkar, MI Jordan NIPS, 1134-1142, 2011	217	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	202	2013
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	184	2014
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	179	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	173	2014
Ensemble nystrom method S Kumar, M Mohri, A Talwalkar Neural Information Processing Systems, 2009	163	2009
The big data bootstrap A Kleiner, A Talwalkar, P Sarkar, M Jordan International Conference on Machine Learning (ICML), 2012	159	2012

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