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Christopher Ré
Christopher Ré
Computer Science, Stanford University
Verified email at cs.stanford.edu - Homepage
Title
Cited by
Cited by
Year
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
2511*2011
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
10902021
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
10702017
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
8392016
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
6512016
Probabilistic databases
D Suciu, D Olteanu, C Ré, C Koch
Synthesis lectures on data management 3 (2), 1-180, 2011
6062011
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
4922012
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
4762006
Hyperbolic graph convolutional neural networks
I Chami, Z Ying, C Ré, J Leskovec
Advances in neural information processing systems 32, 2019
4492019
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
4142014
Holoclean: Holistic data repairs with probabilistic inference
T Rekatsinas, X Chu, IF Ilyas, C Ré
arXiv preprint arXiv:1702.00820, 2017
4082017
Parallel stochastic gradient algorithms for large-scale matrix completion
B Recht, C Ré
Mathematical Programming Computation 5 (2), 201-226, 2013
3772013
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
3552011
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
3342017
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
3232017
Worst-case optimal join algorithms
HQ Ngo, E Porat, C Ré, A Rudra
Journal of the ACM (JACM) 65 (3), 1-40, 2018
3212018
Representation tradeoffs for hyperbolic embeddings
F Sala, C De Sa, A Gu, C Ré
International conference on machine learning, 4460-4469, 2018
3202018
Low-dimensional hyperbolic knowledge graph embeddings
I Chami, A Wolf, DC Juan, F Sala, S Ravi, C Ré
arXiv preprint arXiv:2005.00545, 2020
2692020
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
2682008
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Articles 1–20