-
2
-
-
0031334221
-
Selection of relevant features and examples in machine learning
-
Blum, A., and Langley, P. 1997. Selection of relevant features and examples in machine learning. Artificial Intelligence 97(1-2):245-271.
-
(1997)
Artificial Intelligence
, vol.97
, Issue.1-2
, pp. 245-271
-
-
Blum, A.1
Langley, P.2
-
3
-
-
84899857463
-
CMDragons: Dynamic Passing and Strategy on a Champion Robot Soccer Team
-
Bruce, J. R.; Veloso, M.; and Zickler, S. 2008. CMDragons: Dynamic Passing and Strategy on a Champion Robot Soccer Team. In Proceedings of ICRA '2008.
-
(2008)
Proceedings of ICRA '2008
-
-
Bruce, J.R.1
Veloso, M.2
Zickler, S.3
-
5
-
-
0346450316
-
Automated robot behavior recognition applied to robotic soccer
-
Hollerbach, J, and Koditschek, D, eds, London: Springer-Verlag
-
Han, K., and Veloso, M. 2000. Automated robot behavior recognition applied to robotic soccer. In Hollerbach, J., and Koditschek, D., eds., Robotics Research: the Ninth International Symposium. London: Springer-Verlag. 199-204.
-
(2000)
Robotics Research: The Ninth International Symposium
, pp. 199-204
-
-
Han, K.1
Veloso, M.2
-
7
-
-
0003979126
-
-
Kitano, H, ed, London, UK: Springer-Verlag
-
Kitano, H., ed. 1998. RoboCup-97: Robot Soccer World Cup I. London, UK: Springer-Verlag.
-
(1998)
RoboCup-97: Robot Soccer World Cup I
-
-
-
8
-
-
51349091754
-
An interior-point method for large-scale 11-regularized logistic regression
-
Koh, K.; Kim, S.; and Boyd, S. 2006. An interior-point method for large-scale 11-regularized logistic regression. Under Submission.
-
(2006)
Under Submission
-
-
Koh, K.1
Kim, S.2
Boyd, S.3
-
9
-
-
0142192295
-
Conditional random fields: Probabilistic models for segmenting and labeling sequence data
-
Morgan Kaufmann, San Francisco, CA
-
Lafferty, J.; McCallum, A.; and Pereira, F. 2001. Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In Proc. 18th International Conf. on Machine Learning, 282-289. Morgan Kaufmann, San Francisco, CA.
-
(2001)
Proc. 18th International Conf. on Machine Learning
, pp. 282-289
-
-
Lafferty, J.1
McCallum, A.2
Pereira, F.3
-
10
-
-
84880885580
-
Training conditional random fields using virtual evidence boosting
-
Liao, L.; Choudhury, T.; Fox, D.; and Kautz, H. 2007. Training conditional random fields using virtual evidence boosting. In IJCAI, 2530-2535.
-
(2007)
IJCAI
, pp. 2530-2535
-
-
Liao, L.1
Choudhury, T.2
Fox, D.3
Kautz, H.4
-
12
-
-
0002425879
-
Loopy belief propagation for approximate inference: An empirical study
-
Murphy, K.; Weiss, Y.; and Jordan, M. 1999. Loopy belief propagation for approximate inference: An empirical study. Proceedings of Uncertainty in AI 467-475.
-
(1999)
Proceedings of Uncertainty in AI
, pp. 467-475
-
-
Murphy, K.1
Weiss, Y.2
Jordan, M.3
-
13
-
-
59549087165
-
On discriminative vs. generative classifiers: A comparison of logistic regression and naive bayes
-
Dietterich, T. G, Becker, S, and Ghahramani, Z, eds, Cambridge, MA: MIT Press
-
Ng, A. Y., and Jordan, M. I. 2002. On discriminative vs. generative classifiers: A comparison of logistic regression and naive bayes. In Dietterich, T. G.; Becker, S.; and Ghahramani, Z., eds., Advances in Neural Information Processing Systems 14, 841-848. Cambridge, MA: MIT Press.
-
(2002)
Advances in Neural Information Processing Systems 14
, pp. 841-848
-
-
Ng, A.Y.1
Jordan, M.I.2
-
14
-
-
1942418470
-
Grafting: Fast, incremental feature selection by gradient descent in function space
-
Perkins, S.; Lacker, K.; and Theiler, J. 2003. Grafting: fast, incremental feature selection by gradient descent in function space. The Journal of Machine Learning Research 3:1333-1356.
-
(2003)
The Journal of Machine Learning Research
, vol.3
, pp. 1333-1356
-
-
Perkins, S.1
Lacker, K.2
Theiler, J.3
-
15
-
-
33750032384
-
An introduction to conditional random fields for relational learning
-
Getoor, L, and Taskar, B, eds, MIT Press
-
Sutton, C., and McCallum, A. 2006. An introduction to conditional random fields for relational learning. In Getoor, L., and Taskar, B., eds., Introduction to Statistical Relational Learning. MIT Press.
-
(2006)
Introduction to Statistical Relational Learning
-
-
Sutton, C.1
McCallum, A.2
-
16
-
-
33947615175
-
Dynamic conditional random fields: Factorized probabilistic models for labeling and segmenting sequence data
-
Sutton, C.; McCallum, A.; and Rohanimanesh, K. 2007. Dynamic conditional random fields: Factorized probabilistic models for labeling and segmenting sequence data. The Journal of Machine Learning Research 8:693-723.
-
(2007)
The Journal of Machine Learning Research
, vol.8
, pp. 693-723
-
-
Sutton, C.1
McCallum, A.2
Rohanimanesh, K.3
-
18
-
-
84856105124
-
Conditional random fields for activity recogntion
-
Vail, D. L.; Veloso, M. M.; and Lafferty, J. D. 2007. Conditional random fields for activity recogntion. In AAMAS.
-
(2007)
AAMAS
-
-
Vail, D.L.1
Veloso, M.M.2
Lafferty, J.D.3
|