Christopher Ré

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Citations	26378	18924
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Ce ZhangETH ZurichVerified email at inf.ethz.ch
Sen WuComputer Science, Stanford UniversityVerified email at cs.stanford.edu
Feng NiuUniversity of Wisconsin-MadisonVerified email at cs.wisc.edu
Atri RudraProfessor, CSE, University at BuffaloVerified email at buffalo.edu
Kunle OlukotunCadence Design Systems Professor of Computer Science, Stanford UniversityVerified email at stanford.edu
Benjamin RechtAssociate Professor of EECS, University of California, BerkeleyVerified email at eecs.berkeley.edu
Jude ShavlikProfessor of Computer Science and of Biostatistics & Medical Informatics, University of WisconsinVerified email at cs.wisc.edu
Michael CafarellaAssociate Professor of Computer Science, University of MichiganVerified email at umich.edu
Arun KumarUniversity of California, San DiegoVerified email at eng.ucsd.edu
Jaeho ShinEvidently, Inc.Verified email at cs.stanford.edu
Stephen WrightDepartment of Computer Sciences and Wisconsin Institute for Discovery, University of WisconsinVerified email at cs.wisc.edu
Manas JoglekarPhD, Stanford UniversityVerified email at stanford.edu
Victor BittorfFacebookVerified email at fb.com
Magdalena BalazinskaUniversity of WashingtonVerified email at cs.washington.edu
Ioannis (Yannis) MitliagkasAssociate Professor at Mila, University of MontréalVerified email at iro.umontreal.ca
Dolan AntenucciUniversity of MichiganVerified email at umich.edu
Joseph HellersteinJim Gray Professor of Computer Science, UC BerkeleyVerified email at berkeley.edu
Srikrishna SridharAppleVerified email at tetra.ai
Ji LiuMetaVerified email at meta.com
Xixuan (Aaron) Feng 冯熙铉Software Engineer and Researcher at Megagon Labs

Christopher Ré

Computer Science, Stanford University

Verified email at cs.stanford.edu - Homepage

machine learning machine learning systems data data management


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Hogwild: A lock-free approach to parallelizing stochastic gradient descent F Niu, B Recht, C Ré, S Wright Advances in Neural Information Processing Systems, 693-701, 2011	2524*	2011
Snorkel: Rapid training data creation with weak supervision A Ratner, SH Bach, H Ehrenberg, J Fries, S Wu, C Ré Proceedings of the VLDB Endowment. International Conference on Very Large …, 2017	1057	2017
On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2021	1056	2021
Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features KH Yu, C Zhang, GJ Berry, RB Altman, C Ré, DL Rubin, M Snyder Nature communications 7 (1), 12474, 2016	833	2016
Incremental knowledge base construction using DeepDive C De Sa, A Ratner, C Ré, J Shin, F Wang, S Wu, C Zhang The VLDB Journal 26, 81-105, 2017	788*	2017
Data programming: Creating large training sets, quickly AJ Ratner, CM De Sa, S Wu, D Selsam, C Ré Advances in neural information processing systems 29, 2016	644	2016
Probabilistic databases D Suciu, D Olteanu, C Ré, C Koch Synthesis lectures on data management 3 (2), 1-180, 2011	603	2011
The MADlib analytics library or MAD skills, the SQL J Hellerstein, C Ré, F Schoppmann, DZ Wang, E Fratkin, A Gorajek, ... arXiv preprint arXiv:1208.4165, 2012	490	2012
Efficient top-k query evaluation on probabilistic data C Re, N Dalvi, D Suciu 2007 IEEE 23rd International Conference on Data Engineering, 886-895, 2006	474	2006
Hyperbolic graph convolutional neural networks I Chami, Z Ying, C Ré, J Leskovec Advances in neural information processing systems 32, 2019	439	2019
An asynchronous parallel stochastic coordinate descent algorithm J Liu, S Wright, C Ré, V Bittorf, S Sridhar International Conference on Machine Learning, 469-477, 2014	413	2014
Holoclean: Holistic data repairs with probabilistic inference T Rekatsinas, X Chu, IF Ilyas, C Ré arXiv preprint arXiv:1702.00820, 2017	404	2017
Parallel stochastic gradient algorithms for large-scale matrix completion B Recht, C Ré Mathematical Programming Computation 5 (2), 201-226, 2013	376	2013
Tuffy: Scaling up statistical inference in markov logic networks using an rdbms F Niu, C Ré, AH Doan, J Shavlik arXiv preprint arXiv:1104.3216, 2011	355	2011
Learning to compose domain-specific transformations for data augmentation AJ Ratner, H Ehrenberg, Z Hussain, J Dunnmon, C Ré Advances in neural information processing systems 30, 2017	329	2017
Dawnbench: An end-to-end deep learning benchmark and competition C Coleman, D Narayanan, D Kang, T Zhao, J Zhang, L Nardi, P Bailis, ... Training 100 (101), 102, 2017	320	2017
Worst-case optimal join algorithms HQ Ngo, E Porat, C Ré, A Rudra Journal of the ACM (JACM) 65 (3), 1-40, 2018	319	2018
Representation tradeoffs for hyperbolic embeddings F Sala, C De Sa, A Gu, C Ré International conference on machine learning, 4460-4469, 2018	315	2018
Event queries on correlated probabilistic streams C Ré, J Letchner, M Balazinksa, D Suciu Proceedings of the 2008 ACM SIGMOD international conference on Management of …, 2008	268	2008
Low-dimensional hyperbolic knowledge graph embeddings I Chami, A Wolf, DC Juan, F Sala, S Ravi, C Ré arXiv preprint arXiv:2005.00545, 2020	266	2020

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