-
2
-
-
84858012279
-
Scalable inference in latent variable models
-
Amr Ahmed, Moahmed Aly, Joseph Gonzalez, Shravan Narayanamurthy, and Alexander J. Smola. Scalable inference in latent variable models. In WSDM, pages 123-132, 2012.
-
(2012)
WSDM
, pp. 123-132
-
-
Ahmed, A.1
Aly, M.2
Gonzalez, J.3
Narayanamurthy, S.4
Smola, A.J.5
-
3
-
-
84871948324
-
-
arXiv preprint arXiv:1204.6703
-
Animashree Anandkumar, Dean P Foster, Daniel Hsu, Sham M Kakade, and Yi-Kai Liu. Two svds suffice: Spectral decompositions for probabilistic topic modeling and latent dirichlet allocation. arXiv preprint arXiv:1204.6703, 2012.
-
(2012)
Two Svds Suffice: Spectral Decompositions for Probabilistic Topic Modeling and Latent Dirichlet Allocation
-
-
Anandkumar, A.1
Foster, D.P.2
Hsu, D.3
Kakade, S.M.4
Liu, Y.-K.5
-
5
-
-
85092764449
-
Solving the straggler problem with bounded stale-ness
-
To appear
-
James Cipar, Qirong Ho, Jin Kyu Kim, Seunghak Lee, Gregory R Ganger, Garth Gibson, Kimberly Keeton, and Eric Xing. Solving the straggler problem with bounded stale-ness. In To appear in HotOS 14, 2013.
-
(2013)
HotOS 14
-
-
Cipar, J.1
Ho, Q.2
Kim, J.K.3
Lee, S.4
Ganger, G.R.5
Gibson, G.6
Keeton, K.7
Xing, E.8
-
6
-
-
84877760312
-
Large scale distributed deep networks
-
J Dean, G Corrado, R Monga, K Chen, M Devin, Q Le, M Mao, M Ranzato, A Senior, P Tucker, K Yang, and A Ng. Large scale distributed deep networks. In Advances in Neural Information Processing Systems 25, 2012.
-
(2012)
Advances in Neural Information Processing Systems
, vol.25
-
-
Dean, J.1
Corrado, G.2
Monga, R.3
Chen, K.4
Devin, M.5
Le, Q.6
Mao, M.7
Ranzato, M.8
Senior, A.9
Tucker, P.10
Yang, K.11
Ng, A.12
-
7
-
-
85198028989
-
ImageNet: A large-scale hierarchical image database
-
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei. ImageNet: A Large-Scale Hierarchical Image Database. In CVPR09, 2009.
-
(2009)
CVPR09
-
-
Deng, J.1
Dong, W.2
Socher, R.3
Li, L.-J.4
Li, K.5
Fei-Fei, L.6
-
8
-
-
80052668032
-
Large-scale matrix factorization with distributed stochastic gradient descent
-
New York, NY, USA ACM
-
Rainer Gemulla, Erik Nijkamp, Peter J. Haas, and Yannis Sismanis. Large-scale matrix factorization with distributed stochastic gradient descent. In Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD '11, pages 69-77, New York, NY, USA, 2011. ACM.
-
(2011)
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '11
, pp. 69-77
-
-
Gemulla, R.1
Nijkamp, E.2
Haas, P.J.3
Sismanis, Y.4
-
9
-
-
84898988368
-
More effective distributed ML via a stale synchronous parallel parameter server
-
Q. Ho, J. Cipar, H. Cui, J.-K. Kim, S. Lee, P. B. Gibbons, G. Gibson, G. R. Ganger, and E. P. Xing. More effective distributed ml via a stale synchronous parallel parameter server. In Advances in Neural Information Processing Systems 26, 2013.
-
(2013)
Advances in Neural Information Processing Systems
, vol.26
-
-
Ho, Q.1
Cipar, J.2
Cui, H.3
Kim, J.-K.4
Lee, S.5
Gibbons, P.B.6
Gibson, G.7
Ganger, G.R.8
Xing, E.P.9
-
11
-
-
0037313218
-
Dictionary learning algorithms for sparse representation
-
February
-
Kenneth Kreutz-Delgado, Joseph F. Murray, Bhaskar D. Rao, Kjersti Engan, Te-Won Lee, and Terrence J. Sejnowski. Dictionary learning algorithms for sparse representation. Neural Comput., 15(2):349-396, February 2003.
-
(2003)
Neural Comput.
, vol.15
, Issue.2
, pp. 349-396
-
-
Kreutz-Delgado, K.1
Murray, J.F.2
Rao, B.D.3
Engan, K.4
Lee, T.-W.5
Sejnowski, T.J.6
-
15
-
-
84863735533
-
Distributed GraphLab: A framework for machine learning and data mining in the cloud
-
Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny Bickson, Carlos Guestrin, and Joseph M. Hellerstein. Distributed GraphLab: A Framework for Machine Learning and Data Mining in the Cloud. PVLDB, 2012.
-
(2012)
PVLDB
-
-
Low, Y.1
Gonzalez, J.2
Kyrola, A.3
Bickson, D.4
Guestrin, C.5
Hellerstein, J.M.6
-
17
-
-
85162467517
-
Hogwild!: A lock-free approach to parallelizing stochastic gradient descent
-
Feng Niu, Benjamin Recht, Christopher Ré, and Stephen J Wright. Hogwild!: A lock-free approach to parallelizing stochastic gradient descent. In NIPS, 2011.
-
(2011)
NIPS
-
-
Niu, F.1
Recht, B.2
Ré, C.3
Wright, S.J.4
-
19
-
-
85161967549
-
Parallelized stochastic gradient descent
-
Martin Zinkevich, Markus Weimer, Alex Smola, and Lihong Li. Parallelized stochastic gradient descent. Advances in Neural Information Processing Systems, 23(23):1-9, 2010.
-
(2010)
Advances in Neural Information Processing Systems
, vol.23
, Issue.23
, pp. 1-9
-
-
Zinkevich, M.1
Weimer, M.2
Smola, A.3
Li, L.4
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