Följ
Christopher Ré
Christopher Ré
Computer Science, Stanford University
Verifierad e-postadress på cs.stanford.edu - Startsida
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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
2403*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
8662017
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 (1), 81-105, 2017
741*2017
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), 1-10, 2016
7342016
Probabilistic databases
D Suciu, D Olteanu, C Ré, C Koch
Synthesis lectures on data management 3 (2), 1-180, 2011
5832011
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
5522016
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
4682012
Efficient top-k query evaluation on probabilistic data
C Re, N Dalvi, D Suciu
2007 IEEE 23rd International Conference on Data Engineering, 886-895, 2007
4682007
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
3882014
Parallel stochastic gradient algorithms for large-scale matrix completion
B Recht, C Ré
Mathematical Programming Computation 5 (2), 201-226, 2013
3642013
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
3482011
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
3432021
Holoclean: Holistic data repairs with probabilistic inference
T Rekatsinas, X Chu, IF Ilyas, C Ré
arXiv preprint arXiv:1702.00820, 2017
3432017
Hyperbolic graph convolutional neural networks
I Chami, Z Ying, C Ré, J Leskovec
Advances in neural information processing systems 32, 2019
3122019
Worst-case optimal join algorithms
HQ Ngo, E Porat, C Ré, A Rudra
Journal of the ACM (JACM) 65 (3), 1-40, 2018
2842018
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
2782017
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
2732017
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
2652008
Factoring nonnegative matrices with linear programs
B Recht, C Re, J Tropp, V Bittorf
Advances in neural information processing systems 25, 2012
2592012
MYSTIQ: a system for finding more answers by using probabilities
J Boulos, N Dalvi, B Mandhani, S Mathur, C Re, D Suciu
Proceedings of the 2005 ACM SIGMOD international conference on Management of …, 2005
2572005
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Artiklar 1–20