-
1
-
-
74549196844
-
The power of negative thinking: Exploiting label disagreement in the min-cut classification framework
-
Mohit Bansal, Clair Cardie, and Lillian Lee. 2008. The power of negative thinking: Exploiting label disagreement in the min-cut classification framework. In Proc. of COLING.
-
(2008)
Proc. of COLING
-
-
Bansal, M.1
Cardie, C.2
Lee, L.3
-
4
-
-
84897558007
-
Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures
-
James Bergstra, Daniel Yamins, and David Cox. 2013. Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures. In Proc. of ICML.
-
(2013)
Proc. of ICML.
-
-
Bergstra, J.1
Yamins, D.2
Cox, D.3
-
5
-
-
33750264215
-
Combined optimization of feature selection and algorithm parameters in machine learning of language
-
Walter Daelemans, Veronique Hoste, Fien De Meulder, and Bart Naudts. 2003. Combined optimization of feature selection and algorithm parameters in machine learning of language. In Proc. of ECML.
-
(2003)
Proc. of ECML.
-
-
Daelemans, W.1
Hoste, V.2
De Meulder, F.3
Naudts, B.4
-
6
-
-
84867123033
-
Training restricted Boltzmann machines on word observations
-
George E. Dahl, Ryan P. Adams, and Hugo Larochelle. 2012. Training restricted Boltzmann machines on word observations. In Proc. of ICML.
-
(2012)
Proc. of ICML.
-
-
Dahl, G.E.1
Adams, R.P.2
Larochelle, H.3
-
8
-
-
84856930049
-
Sequential model-based optimization for general algorithm configuration
-
Frank Hutter, Holger H. Hoos, and Kevin Leyton-Brown. 2011. Sequential model-based optimization for general algorithm configuration. In Proc. of LION.
-
(2011)
Proc. of LION.
-
-
Hutter, F.1
Hoos, H.H.2
Leyton-Brown, K.3
-
9
-
-
84960120039
-
Effective use of word order for text categorization with convolutional neural networks
-
Rie Johnson and Tong Zhang. 2015. Effective use of word order for text categorization with convolutional neural networks. In Proc. of NAACL.
-
(2015)
Proc. of NAACL.
-
-
Johnson, R.1
Zhang, T.2
-
10
-
-
0035577808
-
A taxonomy of global optimization methods based on response surfaces
-
Donald R. Jones. 2001. A taxonomy of global optimization methods based on response surfaces. Journal of Global Optimization, 21:345-385.
-
(2001)
Journal of Global Optimization
, vol.21
, pp. 345-385
-
-
Jones, D.R.1
-
11
-
-
85142688646
-
Newsweeder: Learning to filter netnews
-
Ken Lang. 1995. Newsweeder: Learning to filter netnews. In Proc. of ICML.
-
(1995)
Proc. of ICML.
-
-
Lang, K.1
-
12
-
-
56449110012
-
Classification using discriminative restricted Boltzmann machines
-
Hugo Larochelle and Yoshua Bengio. 2008. Classification using discriminative restricted Boltzmann machines. In Proc. of ICML.
-
(2008)
Proc. of ICML.
-
-
Larochelle, H.1
Bengio, Y.2
-
13
-
-
84919829999
-
Distributed representations of sentences and documents
-
Quoc V. Le and Tomas Mikolov. 2014. Distributed representations of sentences and documents. In Proc. of ICML.
-
(2014)
Proc. of ICML.
-
-
Le, Q.V.1
Mikolov, T.2
-
15
-
-
84859023447
-
Learning word vectors for sentiment analysis
-
Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. 2011. Learning word vectors for sentiment analysis. In Proc. of ACL.
-
(2011)
Proc. of ACL.
-
-
Maas, A.L.1
Daly, R.E.2
Pham, P.T.3
Huang, D.4
Ng, A.Y.5
Potts, C.6
-
16
-
-
85015450140
-
Hidden factors and hidden topics: Understanding rating dimensions with review text
-
Julian McAuley and Jure Leskovec. 2013. Hidden factors and hidden topics: understanding rating dimensions with review text. In Proc. of Rec Sys.
-
(2013)
Proc. of Rec Sys.
-
-
McAuley, J.1
Leskovec, J.2
-
19
-
-
84869201485
-
Practical Bayesian optimization of machine learning algorithms
-
Jasper Snoek, Hugo Larrochelle, and Ryan P. Adams. 2012. Practical Bayesian optimization of machine learning algorithms. In NIPS.
-
(2012)
NIPS
-
-
Snoek, J.1
Larrochelle, H.2
Adams, R.P.3
-
21
-
-
84870715081
-
Semantic compositionality through recursive matrix-vector spaces
-
Richard Socher, Brody Huval, Christopher D. Manning, and Andrew Y Ng. 2012. Semantic compositionality through recursive matrix-vector spaces. In Proc. of EMNLP.
-
(2012)
Proc. of EMNLP.
-
-
Socher, R.1
Huval, B.2
Manning, C.D.3
Ng, A.Y.4
-
22
-
-
84926358845
-
Recursive deep models for semantic compositionality over a sentiment treebank
-
Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Chris Manning, Andrew Ng, and Chris Potts. 2013. Recursive deep models for semantic compositionality over a sentiment treebank. In Proc. of EMNLP.
-
(2013)
Proc. of EMNLP.
-
-
Socher, R.1
Perelygin, A.2
Wu, J.3
Chuang, J.4
Manning, C.5
Ng, A.6
Potts, C.7
-
23
-
-
84937874740
-
Learning distributed representations for structured output prediction
-
Vivek Srikumar and Christopher D. Manning. 2014. Learning distributed representations for structured output prediction. In NIPS.
-
(2014)
NIPS
-
-
Srikumar, V.1
Manning, C.D.2
-
24
-
-
77956501313
-
Gaussian process optimization in the bandit setting: No regret and experimental design
-
Niranjan Srinivas, Andreas Krause, Sham Kakade, and Matthias Seeger. 2010. Gaussian process optimization in the bandit setting: No regret and experimental design. In Proc. of ICML.
-
(2010)
Proc. of ICML.
-
-
Srinivas, N.1
Krause, A.2
Kakade, S.3
Seeger, M.4
-
25
-
-
84898939805
-
Multi-task Bayesian optimization
-
Kevin Swersky, Jasper Snoek, and Ryan P. Adams. 2013. Multi-task Bayesian optimization. In NIPS.
-
(2013)
NIPS
-
-
Swersky, K.1
Snoek, J.2
Adams, R.P.3
-
26
-
-
80053357527
-
Get out the vote: Determining support or opposition from congressional floor-debate transcripts
-
Matt Thomas, Bo Pang, and Lilian Lee. 2006. Get out the vote: Determining support or opposition from congressional floor-debate transcripts. In Proc. of EMNLP.
-
(2006)
Proc. of EMNLP
-
-
Thomas, M.1
Pang, B.2
Lee, L.3
-
27
-
-
67650938640
-
An informational approach to the global optimization of expensive-to-evaluate functions
-
Julien Villemonteix, Emmanuel Vazquez, and Eric Walter. 2009. An informational approach to the global optimization of expensive-to-evaluate functions. Journal of Global Optimization, 44(4):509-534.
-
(2009)
Journal of Global Optimization
, vol.44
, Issue.4
, pp. 509-534
-
-
Villemonteix, J.1
Vazquez, E.2
Walter, E.3
-
28
-
-
84875872773
-
Baselines and bigrams: Simple, good sentiment and topic classification
-
Sida Wang and Christopher D. Manning. 2012. Baselines and bigrams: Simple, good sentiment and topic classification. In Proc. of ACL.
-
(2012)
Proc. of ACL.
-
-
Wang, S.1
Manning, C.D.2
-
29
-
-
84255163690
-
Multi-level structured models for document sentiment classification
-
Ainur Yessenalina, Yisong Yue, and Claire Cardie. 2010. Multi-level structured models for document sentiment classification. In Proc. of EMNLP.
-
(2010)
Proc. of EMNLP.
-
-
Yessenalina, A.1
Yue, Y.2
Cardie, C.3
-
30
-
-
84944206615
-
Efficient transfer learning method for automatic hyperparameter tuning
-
Dani Yogatama and Gideon Mann. 2014. Efficient transfer learning method for automatic hyperparameter tuning. In Proc. of AISTATS.
-
(2014)
Proc. of AISTATS.
-
-
Yogatama, D.1
Mann, G.2
|