Fast time series classification using numerosity reduction X Xi, E Keogh, C Shelton, L Wei, CA Ratanamahatana Proceedings of the 23rd international conference on Machine learning, 1033-1040, 2006 | 716 | 2006 |
Continuous time Bayesian networks U Nodelman, CR Shelton, D Koller Uncertainty in Artificial Intelligence, 2002 | 386* | 2002 |
Momentum control for balance A Macchietto, V Zordan, CR Shelton ACM SIGGRAPH 2009 papers, 1-8, 2009 | 272 | 2009 |
A social reinforcement learning agent C Isbell, CR Shelton, M Kearns, S Singh, P Stone Proceedings of the fifth international conference on Autonomous agents, 377-384, 2001 | 223 | 2001 |
Annotating genes of known and unknown function by large-scale coexpression analysis K Horan, C Jang, J Bailey-Serres, R Mittler, C Shelton, JF Harper, JK Zhu, ... Plant physiology 147 (1), 41-57, 2008 | 211 | 2008 |
Automated, highly-accurate, bug assignment using machine learning and tossing graphs P Bhattacharya, I Neamtiu, CR Shelton Journal of Systems and Software 85 (10), 2275-2292, 2012 | 189 | 2012 |
Learning continuous time Bayesian networks U Nodelman, CR Shelton, D Koller Uncertainty in Artificial Intelligence, 2003 | 184* | 2003 |
Improving Multi-target Tracking via Social Grouping Z Qin, CR Shelton IEEE Conference on Computer Vision and Pattern Recognition, 2012 | 179 | 2012 |
Cobot in LambdaMOO: An adaptive social statistics agent CL Isbell, M Kearns, S Singh, CR Shelton, P Stone, D Kormann Autonomous Agents and Multi-Agent Systems 13, 327-354, 2006 | 153 | 2006 |
Morphable surface models CR Shelton International Journal of Computer Vision 38, 75-91, 2000 | 139 | 2000 |
A perturbation scheme for spherical arrangements with application to molecular modeling D Halperin, CR Shelton Proceedings of the thirteenth annual symposium on Computational geometry …, 1997 | 122 | 1997 |
A continuation method for Nash equilibria in structured games B Blum, CR Shelton, D Koller Journal of Artificial Intelligence Research 25, 457-502, 2006 | 114 | 2006 |
Intrusion detection using continuous time Bayesian networks J Xu, CR Shelton Journal of Artificial Intelligence Research 39, 745-774, 2010 | 106 | 2010 |
Importance sampling for reinforcement learning with multiple objectives CR Shelton | 105 | 2001 |
Expectation maximization and complex duration distributions for continuous time Bayesian networks U Nodelman, CR Shelton, D Koller Uncertainty in Artificial Intelligence, 2005 | 103* | 2005 |
An electronic market-maker NT Chan, C Shelton | 101 | 2001 |
Machine learning, machine vision, and the brain T Poggio, CR Shelton AI Magazine 20 (3), 37-37, 1999 | 100 | 1999 |
Learning from scarce experience L Peshkin, CR Shelton International Conference on Machine Learning, 2002 | 96 | 2002 |
Rapid: Randomized pharmacophore identification for drug design PW Finn, LE Kavraki, JC Latombe, R Motwani, C Shelton, ... Proceedings of the thirteenth annual symposium on Computational geometry …, 1997 | 95 | 1997 |
Expectation propagation for continuous time Bayesian networks U Nodelman, D Koller, CR Shelton Uncertainty in Artificial Intelligence, 2005 | 91* | 2005 |