-
2
-
-
85152577740
-
Generalizing from case studies: A case study
-
Aha DW (1992) Generalizing from case studies: a case study. In: ML, pp 1–10
-
(1992)
ML
, pp. 1-10
-
-
Aha, D.W.1
-
4
-
-
0034241361
-
Gradient-based optimization of hyperparameters
-
Bengio Y (2000) Gradient-based optimization of hyperparameters. Neural Comput 12(8):1889–1900 DOI: 10.1162/089976600300015187
-
(2000)
Neural Comput
, vol.12
, Issue.8
, pp. 1889-1900
-
-
Bengio, Y.1
-
6
-
-
84857855190
-
Random search for hyper-parameter optimization
-
Bergstra J, Bengio Y (2012) Random search for hyper-parameter optimization. JMLR 13:281–305
-
(2012)
JMLR
, vol.13
, pp. 281-305
-
-
Bergstra, J.1
Bengio, Y.2
-
8
-
-
84897558007
-
Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures
-
Bergstra J, Yamins D, Cox DD (2013) Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures. In: Proceedings of ICML’13
-
(2013)
Proceedings of ICML’13
-
-
Bergstra, J.1
Yamins, D.2
Cox, D.D.3
-
10
-
-
33745780108
-
Experiment databases: A novel methodology for experimental research
-
Springer
-
Blockeel H (2006) Experiment databases: a novel methodology for experimental research. In: Knowledge discovery in inductive databases, pp 72–85. Springer
-
(2006)
Knowledge Discovery in Inductive Databases
, pp. 72-85
-
-
Blockeel, H.1
-
11
-
-
84958528434
-
Characterizing the applicability of classification algorithms using meta-level learning
-
Brazdil P, Gama J, Henery B (1994) Characterizing the applicability of classification algorithms using meta-level learning. In: Proceedings of ECML’94, pp 83–102
-
(1994)
Proceedings of ECML’94
, pp. 83-102
-
-
Brazdil, P.1
Gama, J.2
Henery, B.3
-
12
-
-
77958068642
-
-
Brochu E, Cora, V., de Freitas, N (2010) A tutorial on Bayesian optimization of expensive cost functions, with application to active user modeling and hierarchical reinforcement learning. ArXiv preprint, arXiv:1012.2599
-
(2010)
A tutorial on Bayesian optimization of expensive cost functions, with application to active user modeling and hierarchical reinforcement learning
-
-
Brochu, E.1
Cora, V.2
Freitas, N.3
-
14
-
-
84866714584
-
Multi-column deep neural networks for image classification
-
IEEE
-
Ciresan D, Meier U, Schmidhuber J (2012) Multi-column deep neural networks for image classification. In: Proceedings of CVPR’12, pp 3642–3649. IEEE
-
(2012)
Proceedings of CVPR’12
, pp. 3642-3649
-
-
Ciresan, D.1
Meier, U.2
Schmidhuber, J.3
-
17
-
-
84919931099
-
Towards an empirical foundation for assessing Bayesian optimization of hyperparameters
-
Eggensperger K, Feurer M, Hutter F, Bergstra J, Snoek J, Hoos H, Leyton-Brown K (2013) Towards an empirical foundation for assessing Bayesian optimization of hyperparameters. In: NIPS workshop on Bayesian Optimization in Theory and Practice
-
(2013)
NIPS Workshop on Bayesian Optimization in Theory and Practice
-
-
Eggensperger, K.1
Feurer, M.2
Hutter, F.3
Bergstra, J.4
Snoek, J.5
Hoos, H.6
Leyton-Brown, K.7
-
18
-
-
33747185668
-
Using a data metric for preprocessing advice for data mining applications
-
Engels R, Theusinger C (1998) Using a data metric for preprocessing advice for data mining applications. In: Proceedings of ECAI’98, pp 430–434
-
(1998)
Proceedings of ECAI’98
, pp. 430-434
-
-
Engels, R.1
Theusinger, C.2
-
19
-
-
84905846583
-
Analysing differences between algorithm configurations through ablation
-
Fawcett C, Hoos H (2013) Analysing differences between algorithm configurations through ablation. In: Proceedings of MIC’13, pp 123–132
-
(2013)
Proceedings of MIC’13
, pp. 123-132
-
-
Fawcett, C.1
Hoos, H.2
-
21
-
-
82455210873
-
Carvalho, A.C.P.L.F.: combining meta-learning and search techniques to select parameters for support vector machines
-
Gomes TAF, Prudêncio RBC, Soares C, Rossi ALD (2012) Carvalho, A.C.P.L.F.: combining meta-learning and search techniques to select parameters for support vector machines. Neurocomputing 75(1):3–13 DOI: 10.1016/j.neucom.2011.07.005
-
(2012)
Neurocomputing
, vol.75
, Issue.1
, pp. 3-13
-
-
Gomes, T.A.F.1
Prudêncio, R.B.C.2
Soares, C.3
Rossi, A.L.D.4
-
23
-
-
54949110721
-
Bayesian models of cognition
-
Sun R, Cambridge University Press, New York, NY, USA
-
Griffiths TL, Kemp C, Tenenbaum JB (2008) Bayesian models of cognition. In: Sun R (ed) Cambridge Handbook of Computational Psychology. Cambridge University Press, New York, NY, USA
-
(2008)
Cambridge Handbook of Computational Psychology
-
-
Griffiths, T.L.1
Kemp, C.2
Tenenbaum, J.B.3
-
24
-
-
84885202726
-
Feedback provision strategies in intelligent tutoring systems based on clustered solution spaces
-
Desel J, Haake JM, Spannagel C, Köllen, Hagen, Germany
-
Gross S, Mokbel B, Hammer B, Pinkwart N (2012) Feedback provision strategies in intelligent tutoring systems based on clustered solution spaces. In: Desel J, Haake JM, Spannagel C (eds) DeLFI 2012: Die 10. e-Learning Fachtagung Informatik, pp 27–38. Köllen, Hagen, Germany
-
(2012)
Delfi 2012: Die 10. E-Learning Fachtagung Informatik
, pp. 27-38
-
-
Gross, S.1
Mokbel, B.2
Hammer, B.3
Pinkwart, N.4
-
25
-
-
58849118133
-
Predicting the performance of learning algorithms using support vector machines as meta-regressors
-
Guerra SB, Prudłncio RB, Ludermir TB (2008) Predicting the performance of learning algorithms using support vector machines as meta-regressors. In: Proceedings of ICANN’08, pp 523–532
-
(2008)
Proceedings of ICANN’08
, pp. 523-532
-
-
Guerra, S.B.1
Prudłncio, R.B.2
Ludermir, T.B.3
-
26
-
-
56549111881
-
A novel LS-SVMs hyper-parameter selection based on particle swarm optimization
-
Guo X, Yang J, Wu C, Wang C, Liang Y (2008) A novel LS-SVMs hyper-parameter selection based on particle swarm optimization. Neurocomputing 71(16):3211–3215 DOI: 10.1016/j.neucom.2008.04.027
-
(2008)
Neurocomputing
, vol.71
, Issue.16
, pp. 3211-3215
-
-
Guo, X.1
Yang, J.2
Wu, C.3
Wang, C.4
Liang, Y.5
-
27
-
-
0001777104
-
Methods for comparison
-
Michie D, Spiegelhalter DJ, Taylor CC, Ellis Horwood, New York
-
Henery RJ (1994) Methods for comparison. In: Michie D, Spiegelhalter DJ, Taylor CC (eds) Machine learning, neural and statistical classification. Ellis Horwood, New York
-
(1994)
Machine Learning, Neural and Statistical Classification
-
-
Henery, R.J.1
-
28
-
-
33745805403
-
A fast learning algorithm for deep belief nets
-
Hinton GE, Osindero S, Teh Y (2006) A fast learning algorithm for deep belief nets. Neural Comput 18(7)
-
(2006)
Neural Comput
, vol.18
, Issue.7
-
-
Hinton, G.E.1
Osindero, S.2
Teh, Y.3
-
29
-
-
0036522441
-
Complexity measures of supervised classification problems
-
Ho TK, Basu M (2002) Complexity measures of supervised classification problems. IEEE Trans Pattern Anal Mach Intell 24(3):289–300 DOI: 10.1109/34.990132
-
(2002)
IEEE Trans Pattern Anal Mach Intell
, vol.24
, Issue.3
, pp. 289-300
-
-
Ho, T.K.1
Basu, M.2
-
30
-
-
84942412216
-
An efficient approach for assessing hyperparameter importance
-
Hutter F, Hoos H, Leyton-Brown K (2014) An efficient approach for assessing hyperparameter importance. In: Proceeding of ICML’14, pp 754–762
-
(2014)
Proceeding of ICML’14
, pp. 754-762
-
-
Hutter, F.1
Hoos, H.2
Leyton-Brown, K.3
-
31
-
-
73649115991
-
ParamILS: an automatic algorithm configuration framework
-
Hutter F, Hoos H, Leyton-Brown K, Stützle T (2009) ParamILS: an automatic algorithm configuration framework. JAIR 36(1):267–306
-
(2009)
JAIR
, vol.36
, Issue.1
, pp. 267-306
-
-
Hutter, F.1
Hoos, H.2
Leyton-Brown, K.3
Stützle, T.4
-
33
-
-
84896062698
-
Identifying key algorithm parameters and instance features using forward selection
-
Hutter F, Hoos HH, Leyton-Brown K (2013) Identifying key algorithm parameters and instance features using forward selection. In: Proceedings of LION-7
-
(2013)
Proceedings of LION-7
-
-
Hutter, F.1
Hoos, H.H.2
Leyton-Brown, K.3
-
34
-
-
0000561424
-
Efficient global optimization of expensive black box functions
-
Jones DR, Schonlau M, Welch WJ (1998) Efficient global optimization of expensive black box functions. Journal of Global Optim 13:455–492 DOI: 10.1023/A:1008306431147
-
(1998)
J Global Optim
, vol.13
, pp. 455-492
-
-
Jones, D.R.1
Schonlau, M.2
Welch, W.J.3
-
35
-
-
0029306995
-
Statlog: comparison of classification algorithms on large real-world problems
-
King RD, Feng C, Sutherland A (1995) Statlog: comparison of classification algorithms on large real-world problems. Appl Artif Intell 9(3):289–333 DOI: 10.1080/08839519508945477
-
(1995)
Appl Artif Intell
, vol.9
, Issue.3
, pp. 289-333
-
-
King, R.D.1
Feng, C.2
Sutherland, A.3
-
38
-
-
0002263996
-
Convolutional networks for images, speech, and time series
-
LeCun Y, Bengio Y (1995) Convolutional networks for images, speech, and time series. Handb Brain Theory Neural Netw 3361:310
-
(1995)
Handb Brain Theory Neural Netw
, vol.3361
, pp. 310
-
-
LeCun, Y.1
Bengio, Y.2
-
41
-
-
0042565834
-
Hierarchical Bayesian inference in the visual cortex
-
Lee TS, Mumford D (2003) Hierarchical Bayesian inference in the visual cortex. J Opt Soc Am A Opt Image Sci Vis 20(7):1434–1448 DOI: 10.1364/JOSAA.20.001434
-
(2003)
J Opt Soc Am A Opt Image Sci Vis
, vol.20
, Issue.7
, pp. 1434-1448
-
-
Lee, T.S.1
Mumford, D.2
-
43
-
-
46749096794
-
Maximal causes for non-linear component extraction
-
Lücke J, Sahani M (2008) Maximal causes for non-linear component extraction. JMLR 9:1227–67
-
(2008)
JMLR
, vol.9
, pp. 1227-1267
-
-
Lücke, J.1
Sahani, M.2
-
44
-
-
0001923944
-
Hoeffding races: Accelerating model selection search for classification and function approximation
-
Maron O, Moore A (1994) Hoeffding races: accelerating model selection search for classification and function approximation. In: Proceeding of NIPS’94, pp 59–66
-
(1994)
Proceeding of NIPS’94
, pp. 59-66
-
-
Maron, O.1
Moore, A.2
-
45
-
-
84878336340
-
Information driven self-organization of complex robotic behaviors
-
Martius G, Der R, Ay N (2013) Information driven self-organization of complex robotic behaviors. PLoS One 8(5), e63,400. DOI10.1371/journal.pone.0063400 DOI: 10.1371/journal.pone.0063400
-
(2013)
Plos One
, vol.8
, Issue.5
-
-
Martius, G.1
Der, R.2
Ay, N.3
-
47
-
-
85162070336
-
Slice sampling covariance hyperparameters of latent Gaussian models
-
Murray I, Adams RP (2010) Slice sampling covariance hyperparameters of latent Gaussian models. In: Proceedings of NIPS’10, pp 1723–1731
-
(2010)
Proceedings of NIPS’10
, pp. 1723-1731
-
-
Murray, I.1
Adams, R.P.2
-
48
-
-
84880053630
-
Self-regulating neurons in the sensorimotor loop
-
Rojas I, Joya G, Gabestany J, (eds), Lecture Notes Computer Science, Springer, Berlin Heidelberg
-
Pasemann F (2013) Self-regulating neurons in the sensorimotor loop. In: Rojas I, Joya G, Gabestany J (eds) Advances in Computational Intelligence, vol 7902., Lecture Notes in Computer ScienceSpringer, Berlin Heidelberg, pp 481–491 DOI: 10.1007/978-3-642-38679-4_48
-
(2013)
Advances in Computational Intelligence
, vol.7902
, pp. 481-491
-
-
Pasemann, F.1
-
49
-
-
33747192617
-
Decision tree-based data characterization for meta-learning
-
Peng Y, Flach PA, Brazdil P, Soares C (2002) Decision tree-based data characterization for meta-learning. In: ECML/PKDD’02 Workshop on Integration and Collaboration Aspects of Data Mining, Decision Support and Meta-Learning, pp 111–122
-
(2002)
ECML/PKDD’02 Workshop on Integration and Collaboration Aspects of Data Mining, Decision Support and Meta-Learning
, pp. 111-122
-
-
Peng, Y.1
Flach, P.A.2
Brazdil, P.3
Soares, C.4
-
52
-
-
84862192698
-
A comprehensive dataset for evaluating approaches of various meta-learning tasks
-
Reif M (2012) A comprehensive dataset for evaluating approaches of various meta-learning tasks. In: Proceedings of ICPRAM’12, vol 1, pp 273–276
-
(2012)
Proceedings of ICPRAM’12
, vol.1
, pp. 273-276
-
-
Reif, M.1
-
53
-
-
84862009037
-
Meta-learning for evolutionary parameter optimization of classifiers
-
Reif M, Shafait F, Dengel A (2012) Meta-learning for evolutionary parameter optimization of classifiers. Mach Learn 87(3):357–380 DOI: 10.1007/s10994-012-5286-7
-
(2012)
Mach Learn
, vol.87
, Issue.3
, pp. 357-380
-
-
Reif, M.1
Shafait, F.2
Dengel, A.3
-
54
-
-
84910651844
-
Deep learning in neural networks: an overview
-
Schmidhuber J (2015) Deep learning in neural networks: an overview. Neural Netw 61:85–117 DOI: 10.1016/j.neunet.2014.09.003
-
(2015)
Neural Netw
, vol.61
, pp. 85-117
-
-
Schmidhuber, J.1
-
55
-
-
0347131360
-
Global versus local search in constrained optimization of computer models
-
Institute of Mathematical Statistics, Hayward, California
-
Schonlau M, Welch WJ, Jones DR (1998) Global versus local search in constrained optimization of computer models. In: New developments and applications in experimental design, vol 34, pp 11–25. Institute of Mathematical Statistics, Hayward, California
-
(1998)
New Developments and Applications in Experimental Design
, vol.34
, pp. 11-25
-
-
Schonlau, M.1
Welch, W.J.2
Jones, D.R.3
-
56
-
-
84908179317
-
A truncated em approach for spike-and-slab sparse coding
-
Sheikh AS, Shelton JA, Lücke J (2014) A truncated em approach for spike-and-slab sparse coding. JMLR 15:2653–2687
-
(2014)
JMLR
, vol.15
, pp. 2653-2687
-
-
Sheikh, A.S.1
Shelton, J.A.2
Lücke, J.3
-
60
-
-
49749086726
-
Cross-disciplinary perspectives on meta-learning for algorithm selection
-
Smith-Miles K (2009) Cross-disciplinary perspectives on meta-learning for algorithm selection. ACM Computing Surveys 41(1), 6:1–6:25
-
(2009)
ACM Computing Surveys
, vol.41
, Issue.1
, pp. 1-6
-
-
Smith-Miles, K.1
-
62
-
-
77956501313
-
Gaussian process optimization in the bandit setting: No regret and experimental design
-
Srinivas N, Krause A, Kakade S, Seeger M (2010) Gaussian process optimization in the bandit setting: No regret and experimental design. In: Proceedings of ICML’10
-
(2010)
Proceedings of ICML’10
-
-
Srinivas, N.1
Krause, A.2
Kakade, S.3
Seeger, M.4
-
63
-
-
84904163933
-
Dropout: a simple way to prevent neural networks from overfitting
-
Srivastava N, Hinton G, Krizhevsky A, Sutskever I, Salakhutdinov R (2014) Dropout: a simple way to prevent neural networks from overfitting. JMLR 15(1):1929–1958
-
(2014)
JMLR
, vol.15
, Issue.1
, pp. 1929-1958
-
-
Srivastava, N.1
Hinton, G.2
Krizhevsky, A.3
Sutskever, I.4
Salakhutdinov, R.5
-
68
-
-
84862023028
-
Experiment databases: a new way to share, organize and learn from experiments
-
Vanschoren J, Blockeel H, Pfahringer B, Holmes G (2012) Experiment databases: a new way to share, organize and learn from experiments. Machine Learning 87(2):127–158 DOI: 10.1007/s10994-011-5277-0
-
(2012)
Mach Learn
, vol.87
, Issue.2
, pp. 127-158
-
-
Vanschoren, J.1
Blockeel, H.2
Pfahringer, B.3
Holmes, G.4
-
69
-
-
0036791948
-
A perspective view and survey of meta-learning
-
Vilalta R, Drissi Y (2002) A perspective view and survey of meta-learning. Artif Intell Rev 18(2):77–95 DOI: 10.1023/A:1019956318069
-
(2002)
Artif Intell Rev
, vol.18
, Issue.2
, pp. 77-95
-
-
Vilalta, R.1
Drissi, Y.2
-
70
-
-
79551480483
-
Stacked denoising autoencoders: learning useful representations in a deep network with a local denoising criterion
-
Vincent P, Larochelle H, Lajoie I, Bengio Y, Manzagol P (2010) Stacked denoising autoencoders: learning useful representations in a deep network with a local denoising criterion. JMLR 11:3371–3408
-
(2010)
JMLR
, vol.11
, pp. 3371-3408
-
-
Vincent, P.1
Larochelle, H.2
Lajoie, I.3
Bengio, Y.4
Manzagol, P.5
-
73
-
-
84955448572
-
Efficient transfer learning method for automatic hyperparameter tuning
-
Yogatama D, Mann G (2014) Efficient transfer learning method for automatic hyperparameter tuning. In: Proceedings of AISTATS’14, pp 1077–1085
-
(2014)
Proceedings of AISTATS’14
, pp. 1077-1085
-
-
Yogatama, D.1
Mann, G.2
|