-
1
-
-
68249088215
-
Model selection for the LS-SVM. Application to handwriting recognition
-
M. Adankon and M. Cheriet. Model selection for the LS-SVM. application to handwriting recognition. Pattern Recognition, 42(12):3264-3270, 2009.
-
(2009)
Pattern Recognition
, vol.42
, Issue.12
, pp. 3264-3270
-
-
Adankon, M.1
Cheriet, M.2
-
3
-
-
0034241361
-
Gradient-based optimization of hyperparameters
-
Y. Bengio. Gradient-based optimization of hyperparameters. Neural Computation, 12(8):1889-1900, 2000.
-
(2000)
Neural Computation
, vol.12
, Issue.8
, pp. 1889-1900
-
-
Bengio, Y.1
-
5
-
-
84857855190
-
Random search for hyper-parameter optimization
-
J. Bergstra and Y. Bengio. Random search for hyper-parameter optimization. JMLR, 13:281-305, 2012.
-
(2012)
JMLR
, vol.13
, pp. 281-305
-
-
Bergstra, J.1
Bengio, Y.2
-
6
-
-
2442594524
-
A model selection criterion for classification: Application to HMM topology optimization
-
IEEE
-
A. Biem. A model selection criterion for classification: Application to HMM topology optimization. In Proc. of ICDAR-03, pages 104-108. IEEE, 2003.
-
(2003)
Proc. of ICDAR-03
, pp. 104-108
-
-
Biem, A.1
-
7
-
-
34250108028
-
Model selection and Akaike's information criterion (AIC): The general theory and its analytical extensions
-
H. Bozdogan. Model selection and Akaike's information criterion (AIC): The general theory and its analytical extensions. Psychometrika, 52(3):345-370, 1987.
-
(1987)
Psychometrika
, vol.52
, Issue.3
, pp. 345-370
-
-
Bozdogan, H.1
-
8
-
-
0037361994
-
Ranking learning algorithms: Using IBL and meta-learning on accuracy and time results
-
P. Brazdil, C. Soares, and J. Da Costa. Ranking learning algorithms: Using IBL and meta-learning on accuracy and time results. Machine Learning, 50(3):251-277, 2003.
-
(2003)
Machine Learning
, vol.50
, Issue.3
, pp. 251-277
-
-
Brazdil, P.1
Soares, C.2
Da Costa, J.3
-
9
-
-
77958068642
-
A tutorial on Bayesian optimization of expensive cost functions, with application to active user modeling and hierarchical reinforcement learning
-
Department of Computer Science, University of British Columbia
-
E. Brochu, V. M. Cora, and N. de Freitas. A tutorial on Bayesian optimization of expensive cost functions, with application to active user modeling and hierarchical reinforcement learning. Technical Report UBC TR-2009-23 and arXiv:1012.2599v1, Department of Computer Science, University of British Columbia, 2009.
-
(2009)
Technical Report UBC TR-2009-23 and ArXiv:1012.2599v1
-
-
Brochu, E.1
Cora, V.M.2
De Freitas, N.3
-
11
-
-
84867115523
-
Parallelizing exploration-exploitation tradeoffs with Gaussian process bandit optimization
-
T. Desautels, A. Krause, and J. Burdick. Parallelizing exploration-exploitation tradeoffs with gaussian process bandit optimization. In Proc. of ICML-12, 2012.
-
(2012)
Proc. of ICML-12
-
-
Desautels, T.1
Krause, A.2
Burdick, J.3
-
12
-
-
78649934709
-
-
University of California, Irvine, School of Information and Computer Sciences
-
A. Frank and A. Asuncion. UCI machine learning repository, 2010. URL: http://archive.ics.uci.edu/ml University of California, Irvine, School of Information and Computer Sciences.
-
(2010)
UCI Machine Learning Repository
-
-
Frank, A.1
Asuncion, A.2
-
13
-
-
56549111881
-
A novel LS-SVMs hyper-parameter selection based on particle swarm optimization
-
X. Guo, J. Yang, C. Wu, C. Wang, and Y. Liang. A novel LS-SVMs hyper-parameter selection based on particle swarm optimization. Neurocomputing, 71(16):3211-3215, 2008.
-
(2008)
Neurocomputing
, vol.71
, Issue.16
, pp. 3211-3215
-
-
Guo, X.1
Yang, J.2
Wu, C.3
Wang, C.4
Liang, Y.5
-
14
-
-
76749092270
-
The WEKA data mining software: An update
-
M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, and I. Witten. The WEKA data mining software: An update. ACM SIGKDD Explorations Newsletter, 11(1):10-18, 2009.
-
(2009)
ACM SIGKDD Explorations Newsletter
, vol.11
, Issue.1
, pp. 10-18
-
-
Hall, M.1
Frank, E.2
Holmes, G.3
Pfahringer, B.4
Reutemann, P.5
Witten, I.6
-
15
-
-
84868554032
-
Sequential model-based optimization for general algorithm configuration
-
F. Hutter, H. Hoos, and K. Leyton-Brown. Sequential model-based optimization for general algorithm configuration. In Proc. of LION-5, pages 507-523, 2011.
-
(2011)
Proc. of LION-5
, pp. 507-523
-
-
Hutter, F.1
Hoos, H.2
Leyton-Brown, K.3
-
16
-
-
73649115991
-
ParamILS: An automatic algorithm configuration framework
-
F. Hutter, H. Hoos, K. Leyton-Brown, and T. Stützle. ParamILS: An automatic algorithm configuration framework. JAIR, 36(1):267-306, 2009.
-
(2009)
JAIR
, vol.36
, Issue.1
, pp. 267-306
-
-
Hutter, F.1
Hoos, H.2
Leyton-Brown, K.3
Stützle, T.4
-
19
-
-
85164392958
-
A study of cross-validation and bootstrap for accuracy estimation and model selection
-
R. Kohavi. A study of cross-validation and bootstrap for accuracy estimation and model selection. In Proc. of IJCAI-95, pages 1137-1145, 1995.
-
(1995)
Proc. of IJCAI-95
, pp. 1137-1145
-
-
Kohavi, R.1
-
21
-
-
84864928603
-
Selecting classification algorithms with active testing
-
R. Leite, P. Brazdil, and J. Vanschoren. Selecting classification algorithms with active testing. In Proc. of MLDM-12, pages 117-131, 2012.
-
(2012)
Proc. of MLDM-12
, pp. 117-131
-
-
Leite, R.1
Brazdil, P.2
Vanschoren, J.3
-
22
-
-
80051855151
-
The irace package, iterated race for automatic algorithm configuration
-
Université Libre de Bruxelles, Belgium
-
M. López-Ibáñez, J. Dubois-Lacoste, T. Stützle, and M. Birattari. The irace package, iterated race for automatic algorithm configuration. Technical Report TR/IRIDIA/2011-004, IRIDIA, Université Libre de Bruxelles, Belgium, 2011.
-
(2011)
Technical Report TR/IRIDIA/2011-004, IRIDIA
-
-
López-Ibáñez, M.1
Dubois-Lacoste, J.2
Stützle, T.3
Birattari, M.4
-
23
-
-
0001923944
-
Hoeffding races: Accelerating model selection search for classification and function approximation
-
O. Maron and A. Moore. Hoeffding races: Accelerating model selection search for classification and function approximation. In Proc. of NIPS-94, pages 59-66, 1994.
-
(1994)
Proc. of NIPS-94
, pp. 59-66
-
-
Maron, O.1
Moore, A.2
-
24
-
-
67849122925
-
Regression and time series model selection
-
A. McQuarrie and C. Tsai. Regression and time series model selection. World Scientific, 1998.
-
(1998)
World Scientific
-
-
McQuarrie, A.1
Tsai, C.2
-
26
-
-
85015267174
-
-
T. Schaul, J. Bayer, D. Wierstra, Y. Sun, M. Felder, F. Sehnke, T. Rückstieß, and J. Schmidhuber. PyBrain. JMLR, 2010.
-
(2010)
PyBrain. JMLR
-
-
Schaul, T.1
Bayer, J.2
Wierstra, D.3
Sun, Y.4
Felder, M.5
Sehnke, F.6
Rückstieß, T.7
Schmidhuber, J.8
-
27
-
-
0347131360
-
Global versus local search in constrained optimization of computer models
-
N. Flournoy, W. Rosenberger, and W. Wong, editors, Institute of Mathematical Statistics, Hayward, California
-
M. Schonlau, W. J. Welch, and D. R. Jones. Global versus local search in constrained optimization of computer models. In N. Flournoy, W. Rosenberger, and W. Wong, editors, New Developments and Applications in Experimental Design, volume 34, pages 11-25. Institute of Mathematical Statistics, Hayward, California, 1998.
-
(1998)
New Developments and Applications in Experimental Design
, vol.34
, pp. 11-25
-
-
Schonlau, M.1
Welch, W.J.2
Jones, D.R.3
-
28
-
-
85025617914
-
Opportunity cost in Bayesian optimization
-
Published online
-
J. Snoek, H. Larochelle, and R. Adams. Opportunity cost in Bayesian optimization. In NIPS Workshop on Bayesian Optimization, Sequential Experimental Design, and Bandits, 2011. Published online.
-
(2011)
NIPS Workshop on Bayesian Optimization, Sequential Experimental Design, and Bandits
-
-
Snoek, J.1
Larochelle, H.2
Adams, R.3
-
29
-
-
84869201485
-
Practical Bayesian optimization of machine learning algorithms
-
J. Snoek, H. Larochelle, and R. P. Adams. Practical bayesian optimization of machine learning algorithms. In Proc. of NIPS-12, 2012.
-
(2012)
Proc. of NIPS-12
-
-
Snoek, J.1
Larochelle, H.2
Adams, R.P.3
-
30
-
-
77956501313
-
Gaussian process optimization in the bandit setting: No regret and experimental design
-
N. Srinivas, A. Krause, S. Kakade, and M. Seeger. Gaussian process optimization in the bandit setting: No regret and experimental design. In Proc. of ICML-10, pages 1015-1022, 2010.
-
(2010)
Proc. of ICML-10
, pp. 1015-1022
-
-
Srinivas, N.1
Krause, A.2
Kakade, S.3
Seeger, M.4
-
31
-
-
77955426712
-
Nonlinear regression model generation using hyperparameter optimization
-
V. Strijov and G. Weber. Nonlinear regression model generation using hyperparameter optimization. Computers & Mathematics with Applications, 60(4):981-988, 2010.
-
(2010)
Computers & Mathematics with Applications
, vol.60
, Issue.4
, pp. 981-988
-
-
Strijov, V.1
Weber, G.2
-
32
-
-
0036791948
-
A perspective view and survey of meta-learning
-
Oct
-
R. Vilalta and Y. Drissi. A perspective view and survey of meta-learning. Artif. Intell. Rev., 18(2):77-95, Oct. 2002.
-
(2002)
Artif. Intell. Rev
, vol.18
, Issue.2
, pp. 77-95
-
-
Vilalta, R.1
Drissi, Y.2
-
33
-
-
77958579640
-
Hydra: Automatically configuring algorithms for portfolio-based selection
-
L. Xu, H. H. Hoos, and K. Leyton-Brown. Hydra: Automatically configuring algorithms for portfolio-based selection. In Proc. of AAAI-10, pages 210-216, 2010.
-
(2010)
Proc. of AAAI-10
, pp. 210-216
-
-
Xu, L.1
Hoos, H.H.2
Leyton-Brown, K.3
-
34
-
-
33845263263
-
On model selection consistency of lasso
-
Dec
-
P. Zhao and B. Yu. On model selection consistency of lasso. JMLR, 7:2541-2563, Dec. 2006.
-
(2006)
JMLR
, vol.7
, pp. 2541-2563
-
-
Zhao, P.1
Yu, B.2
|