-
1
-
-
51449109891
-
Phonetic classification using hierarchical, feed-forward, spectro-temporal patch-based architectures
-
Tech. Rep. MIT-CSAIL-TR-2007-019
-
R. Rifkin, J. Bouvrie, K. Schutte, S. Chikkerur, M. Kouh, T. Ezzat, and T. Poggio, "Phonetic classification using hierarchical, feed-forward, spectro-temporal patch-based architectures," Massachusetts Institute of Technology, Tech. Rep. MIT-CSAIL-TR-2007-019, 2007.
-
(2007)
Massachusetts Institute of Technology
-
-
Rifkin, R.1
Bouvrie, J.2
Schutte, K.3
Chikkerur, S.4
Kouh, M.5
Ezzat, T.6
Poggio, T.7
-
2
-
-
0032203257
-
Gradient-based learning applied to document recognition
-
Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner, "Gradient-based learning applied to document recognition," Proceedings of the IEEE, vol. 86, no. 11, 1998.
-
(1998)
Proceedings of the IEEE
, vol.86
, Issue.11
-
-
Lecun, Y.1
Bottou, L.2
Bengio, Y.3
Haffner, P.4
-
3
-
-
34247096930
-
A feedforward architecture accounts for rapid categorization
-
T. Serre, A. Oliva, and T. Poggio, "A feedforward architecture accounts for rapid categorization," Proceedings of the National Academy of Sciences, vol. 104, no. 15, 2007.
-
(2007)
Proceedings of the National Academy of Sciences
, vol.104
, Issue.15
-
-
Serre, T.1
Oliva, A.2
Poggio, T.3
-
4
-
-
33750708213
-
Visual explanation of evidence in additive classifiers
-
IAAI, July
-
B. Poulin, R. Eisner, D. Szafron, P. Lu, R. Greiner, D. Wishart, A. Fyshe, B. Pearcy, C. MAcDonell, and J. Anvik, "Visual explanation of evidence in additive classifiers," in Proceedings of 18th Conference on Innovative Applications of Artificial Intelligence. IAAI, July 2006.
-
(2006)
Proceedings of 18th Conference on Innovative Applications of Artificial Intelligence
-
-
Poulin, B.1
Eisner, R.2
Szafron, D.3
Lu, P.4
Greiner, R.5
Wishart, D.6
Fyshe, A.7
Pearcy, B.8
MacDonell, C.9
Anvik, J.10
-
5
-
-
0028482883
-
Rule generation from neural networks
-
L. Fu, "Rule generation from neural networks," IEEE Transactions on Systems, Man and Cybernetics, vol. 24, no. 8, 1994.
-
(1994)
IEEE Transactions on Systems, Man and Cybernetics
, vol.24
, Issue.8
-
-
Fu, L.1
-
6
-
-
33847275584
-
Unsupervised learning of visual features through spike timing dependent plasticity
-
T. Masquelier and S. Thorpe, "Unsupervised learning of visual features through spike timing dependent plasticity," PLoS Comp. Bio., vol. 3, no. 2, 2007.
-
(2007)
PLoS Comp. Bio
, vol.3
, Issue.2
-
-
Masquelier, T.1
Thorpe, S.2
-
7
-
-
76749170318
-
An efficient explanation of individual classifications using game theory
-
E. Strumbelj and I. Kononenko, "An efficient explanation of individual classifications using game theory," Journal of Machine Learning Research, vol. 11, no. 1, 2010.
-
(2010)
Journal of Machine Learning Research
, vol.11
, Issue.1
-
-
Strumbelj, E.1
Kononenko, I.2
-
8
-
-
77954665728
-
How to explain individual classification decisions
-
D. Baehrens, T. Schroeter, S. Harmeling, M. Kawanabe, K. Hansen, and K. Muller, "How to explain individual classification decisions," Journal of Machine Learning Research, vol. 11, pp. 1803-1831, 2010.
-
(2010)
Journal of Machine Learning Research
, vol.11
, pp. 1803-1831
-
-
Baehrens, D.1
Schroeter, T.2
Harmeling, S.3
Kawanabe, M.4
Hansen, K.5
Muller, K.6
-
9
-
-
0033316361
-
Hierarchical models of object recognition in cortex
-
M. Riesenhuber and T. Poggio, "Hierarchical models of object recognition in cortex," Nature Neuroscience, vol. 2, no. 11, 1999.
-
(1999)
Nature Neuroscience
, vol.2
, Issue.11
-
-
Riesenhuber, M.1
Poggio, T.2
-
11
-
-
0002714543
-
Making large-scale SVM learning practical
-
B. Scholkopf, C. Burges, and A. Smola, Eds. MIT Press
-
T. Joachims, "Making large-scale SVM learning practical." in Advances in Kernel Methods-Support Vector Learning, B. Scholkopf, C. Burges, and A. Smola, Eds. MIT Press, 1999.
-
(1999)
Advances in Kernel Methods-Support Vector Learning
-
-
Joachims, T.1
-
12
-
-
84932617705
-
Learning generative visual models from few training examples: An incremental Bayesian approach tested on 101 object categories
-
L. Fei-Fei, R. Fergus, and P. Perona, "Learning generative visual models from few training examples: an incremental Bayesian approach tested on 101 object categories," in IEEE. CVPR 2004, Workshop on Generative-Model Based Vision, 2004.
-
(2004)
IEEE. CVPR 2004, Workshop on Generative-Model Based Vision
-
-
Fei-Fei, L.1
Fergus, R.2
Perona, P.3
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