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2Nonnegative matrix factorization: A comprehensive review
Y. Wang, and Y. Zhang. IEEE Transactions on Knowledge and Data Engineering, 25 (6): 1336--1353 (2013)
7 years ago by @becker
show all tags
uw_ws17_ml
thema
citedby:scholar:timestamp:2017-9-29
thema:nonnegativematrixfactorization
citedby:scholar:count:234
uw_ws17_mlthemacitedby:scholar:timestamp:2017-9-29thema:nonnegativematrixfactorizationcitedby:scholar:count:234
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3Auto-WEKA: Combined selection and hyperparameter optimization of classification algorithms
C. Thornton, F. Hutter, H. Hoos, and K. Leyton-Brown. Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, page 847--855. ACM, (2013)
7 years ago by @becker
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uw_ws17_ml
thema
citedby:scholar:count:262
citedby:scholar:timestamp:2017-9-29
thema:automl
uw_ws17_mlthemacitedby:scholar:count:262citedby:scholar:timestamp:2017-9-29thema:automl
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15Deepwalk: Online learning of social representations
B. Perozzi, R. Al-Rfou, and S. Skiena. Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, page 701--710. ACM, (2014)
7 years ago by @becker
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uw_ws17_ml
citedby:scholar:count:368
citedby:scholar:timestamp:2017-9-29
uw_ws17_mlcitedby:scholar:count:368citedby:scholar:timestamp:2017-9-29
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2Knowledge vault: A web-scale approach to probabilistic knowledge fusion
X. Dong, E. Gabrilovich, G. Heitz, W. Horn, N. Lao, K. Murphy, T. Strohmann, S. Sun, and W. Zhang. Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, page 601--610. ACM, (2014)
7 years ago by @becker
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thema:probabilisticknowledge
uw_ws17_ml
thema
citedby:scholar:timestamp:2017-9-29
citedby:scholar:count:476
thema:probabilisticknowledgeuw_ws17_mlthemacitedby:scholar:timestamp:2017-9-29citedby:scholar:count:476
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2Never Ending Learning
T. Mitchell, W. Cohen, E. Hruschka Jr, P. Talukdar, J. Betteridge, A. Carlson, B. Mishra, M. Gardner, B. Kisiel, J. Krishnamurthy and 1 other author(s). AAAI, page 2302--2310. (2015)
7 years ago by @becker
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uw_ws17_ml
thema
citedby:scholar:count:165
thema:neverendinglearning
citedby:scholar:timestamp:2017-9-29
uw_ws17_mlthemacitedby:scholar:count:165thema:neverendinglearningcitedby:scholar:timestamp:2017-9-29
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4Fused Matrix Factorization with Geographical and Social Influence in Location-Based Social Networks.
C. Cheng, H. Yang, I. King, and M. Lyu. Aaai, 12, page 17--23. (2012)
7 years ago by @becker
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uw_ws17_ml
citedby:scholar:count:258
citedby:scholar:timestamp:2017-9-29
uw_ws17_mlcitedby:scholar:count:258citedby:scholar:timestamp:2017-9-29
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1Analysis of a random forests model
G. Biau. Journal of Machine Learning Research, 13 (Apr): 1063--1095 (2012)
7 years ago by @becker
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uw_ws17_ml
citedby:scholar:count:341
citedby:scholar:timestamp:2017-9-29
uw_ws17_mlcitedby:scholar:count:341citedby:scholar:timestamp:2017-9-29
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2Tensor decompositions for learning latent variable models.
A. Anandkumar, R. Ge, D. Hsu, S. Kakade, and M. Telgarsky. Journal of Machine Learning Research, 15 (1): 2773--2832 (2014)
7 years ago by @becker
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uw_ws17_ml
citedby:scholar:count:413
citedby:scholar:timestamp:2017-9-29
uw_ws17_mlcitedby:scholar:count:413citedby:scholar:timestamp:2017-9-29
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4Stochastic variational inference
M. Hoffman, D. Blei, C. Wang, and J. Paisley. The Journal of Machine Learning Research, 14 (1): 1303--1347 (2013)
7 years ago by @becker
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uw_ws17_ml
citedby:scholar:count:683
citedby:scholar:timestamp:2017-9-29
uw_ws17_mlcitedby:scholar:count:683citedby:scholar:timestamp:2017-9-29
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7Auto-encoding variational bayes
D. Kingma, and M. Welling. arXiv preprint arXiv:1312.6114, (2013)
7 years ago by @becker
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uw_ws17_ml
citedby:scholar:count:1145
citedby:scholar:timestamp:2017-9-29
uw_ws17_mlcitedby:scholar:count:1145citedby:scholar:timestamp:2017-9-29
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4Stochastic backpropagation and approximate inference in deep generative models
D. Rezende, S. Mohamed, and D. Wierstra. arXiv preprint arXiv:1401.4082, (2014)
7 years ago by @becker
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uw_ws17_ml
citedby:scholar:count:511
citedby:scholar:timestamp:2017-9-29
uw_ws17_mlcitedby:scholar:count:511citedby:scholar:timestamp:2017-9-29
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27Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. Hinton. Advances in neural information processing systems, page 1097--1105. (2012)
7 years ago by @becker
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uw_ws17_ml
citedby:scholar:timestamp:2017-9-29
citedby:scholar:count:15466
uw_ws17_mlcitedby:scholar:timestamp:2017-9-29citedby:scholar:count:15466
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31Distributed representations of words and phrases and their compositionality
T. Mikolov, I. Sutskever, K. Chen, G. Corrado, and J. Dean. Advances in neural information processing systems, page 3111--3119. (2013)
7 years ago by @becker
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uw_ws17_ml
citedby:scholar:count:5162
citedby:scholar:timestamp:2017-9-29
uw_ws17_mlcitedby:scholar:count:5162citedby:scholar:timestamp:2017-9-29
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18Sequence to sequence learning with neural networks
I. Sutskever, O. Vinyals, and Q. Le. Advances in neural information processing systems, page 3104--3112. (2014)
7 years ago by @becker
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thema:sequencetosequencelearning
uw_ws17_ml
citedby:scholar:count:2226
thema
citedby:scholar:timestamp:2017-9-29
thema:sequencetosequencelearninguw_ws17_mlcitedby:scholar:count:2226themacitedby:scholar:timestamp:2017-9-29
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3Large scale distributed deep networks
J. Dean, G. Corrado, R. Monga, K. Chen, M. Devin, M. Mao, A. Senior, P. Tucker, K. Yang, Q. Le and 1 other author(s). Advances in neural information processing systems, page 1223--1231. (2012)
7 years ago by @becker
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thema
citedby:scholar:count:1045
thema:paralellizingneuralnetworks
citedby:scholar:timestamp:2017-9-29
uw_ws17_mlthemacitedby:scholar:count:1045thema:paralellizingneuralnetworkscitedby:scholar:timestamp:2017-9-29
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5Practical bayesian optimization of machine learning algorithms
J. Snoek, H. Larochelle, and R. Adams. Advances in neural information processing systems, page 2951--2959. (2012)
7 years ago by @becker
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uw_ws17_ml
citedby:scholar:count:945
citedby:scholar:timestamp:2017-9-29
uw_ws17_mlcitedby:scholar:count:945citedby:scholar:timestamp:2017-9-29
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7Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio. Advances in neural information processing systems, page 2672--2680. (2014)
7 years ago by @becker
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bmbf
uw_ws17_ml
erp
thema
thema:generativeadversarialnets
citedby:scholar:count:1284
citedby:scholar:timestamp:2017-9-29
bmbfuw_ws17_mlerpthemathema:generativeadversarialnetscitedby:scholar:count:1284citedby:scholar:timestamp:2017-9-29
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6On the difficulty of training recurrent neural networks
R. Pascanu, T. Mikolov, and Y. Bengio. International Conference on Machine Learning, page 1310--1318. (2013)
7 years ago by @becker
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uw_ws17_ml
citedby:scholar:count:644
thema
thema:recurrentneuralnetworks
citedby:scholar:timestamp:2017-9-29
uw_ws17_mlcitedby:scholar:count:644themathema:recurrentneuralnetworkscitedby:scholar:timestamp:2017-9-29
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13Playing atari with deep reinforcement learning
V. Mnih, K. Kavukcuoglu, D. Silver, A. Graves, I. Antonoglou, D. Wierstra, and M. Riedmiller. arXiv preprint arXiv:1312.5602, (2013)
7 years ago by @becker
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thema:deepreinforcementlearning
uw_ws17_ml
thema
citedby:scholar:count:709
citedby:scholar:timestamp:2017-9-29
thema:deepreinforcementlearninguw_ws17_mlthemacitedby:scholar:count:709citedby:scholar:timestamp:2017-9-29
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8Representation learning: A review and new perspectives
Y. Bengio, A. Courville, and P. Vincent. IEEE transactions on pattern analysis and machine intelligence, 35 (8): 1798--1828 (2013)
7 years ago by @becker
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uw_ws17_ml
toread
thema
citedby:scholar:count:2400
thema:representationlearning
citedby:scholar:timestamp:2017-9-29
uw_ws17_mltoreadthemacitedby:scholar:count:2400thema:representationlearningcitedby:scholar:timestamp:2017-9-29
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BibSonomy

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publications (hide)20
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2Nonnegative matrix factorization: A comprehensive review

3Auto-WEKA: Combined selection and hyperparameter optimization of classification algorithms

15Deepwalk: Online learning of social representations

2Knowledge vault: A web-scale approach to probabilistic knowledge fusion

2Never Ending Learning

4Fused Matrix Factorization with Geographical and Social Influence in Location-Based Social Networks.

1Analysis of a random forests model

2Tensor decompositions for learning latent variable models.

4Stochastic variational inference

7Auto-encoding variational bayes

4Stochastic backpropagation and approximate inference in deep generative models

27Imagenet classification with deep convolutional neural networks

31Distributed representations of words and phrases and their compositionality

18Sequence to sequence learning with neural networks

3Large scale distributed deep networks

5Practical bayesian optimization of machine learning algorithms

7Generative adversarial nets

6On the difficulty of training recurrent neural networks

13Playing atari with deep reinforcement learning

8Representation learning: A review and new perspectives

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