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Publication search results
found 135 matches
- 2005
- Pieter Abbeel, Andrew Y. Ng:
Exploration and apprenticeship learning in reinforcement learning. ICML 2005: 1-8 - Brigham S. Anderson, Andrew Moore:
Active learning for Hidden Markov Models: objective functions and algorithms. ICML 2005: 9-16 - Nicos Angelopoulos, James Cussens:
Tempering for Bayesian C&RT. ICML 2005: 17-24 - Fabrizio Angiulli:
Fast condensed nearest neighbor rule. ICML 2005: 25-32 - Francis R. Bach, Michael I. Jordan:
Predictive low-rank decomposition for kernel methods. ICML 2005: 33-40 - Ron Bekkerman, Ran El-Yaniv, Andrew McCallum:
Multi-way distributional clustering via pairwise interactions. ICML 2005: 41-48 - Alina Beygelzimer, Varsha Dani, Thomas P. Hayes, John Langford, Bianca Zadrozny:
Error limiting reductions between classification tasks. ICML 2005: 49-56 - Hendrik Blockeel, David Page, Ashwin Srinivasan:
Multi-instance tree learning. ICML 2005: 57-64 - Michael H. Bowling, Ali Ghodsi, Dana F. Wilkinson:
Action respecting embedding. ICML 2005: 65-72 - Markus Breitenbach, Gregory Z. Grudic:
Clustering through ranking on manifolds. ICML 2005: 73-80 - Will Bridewell, Narges Bani Asadi, Pat Langley, Ljupco Todorovski:
Reducing overfitting in process model induction. ICML 2005: 81-88 - John Burge, Terran Lane:
Learning class-discriminative dynamic Bayesian networks. ICML 2005: 97-104 - Christopher J. C. Burges, Tal Shaked, Erin Renshaw, Ari Lazier, Matt Deeds, Nicole Hamilton, Gregory N. Hullender:
Learning to rank using gradient descent. ICML 2005: 89-96 - Sylvain Calinon, Aude Billard:
Recognition and reproduction of gestures using a probabilistic framework combining PCA, ICA and HMM. ICML 2005: 105-112 - Michael Carney, Padraig Cunningham, Jim Dowling, Ciaran Lee:
Predicting probability distributions for surf height using an ensemble of mixture density networks. ICML 2005: 113-120 - Yu-Han Chang, Leslie Pack Kaelbling:
Hedged learning: regret-minimization with learning experts. ICML 2005: 121-128 - Li Cheng, Feng Jiao, Dale Schuurmans, Shaojun Wang:
Variational Bayesian image modelling. ICML 2005: 129-136 - Wei Chu, Zoubin Ghahramani:
Preference learning with Gaussian processes. ICML 2005: 137-144 - Wei Chu, S. Sathiya Keerthi:
New approaches to support vector ordinal regression. ICML 2005: 145-152 - Corinna Cortes, Mehryar Mohri, Jason Weston:
A general regression technique for learning transductions. ICML 2005: 153-160 - Jacob W. Crandall, Michael A. Goodrich:
Learning to compete, compromise, and cooperate in repeated general-sum games. ICML 2005: 161-168 - Hal Daumé III, Daniel Marcu:
Learning as search optimization: approximate large margin methods for structured prediction. ICML 2005: 169-176 - Adam Drake, Dan Ventura:
A practical generalization of Fourier-based learning. ICML 2005: 185-192 - Kurt Driessens, Saso Dzeroski:
Combining model-based and instance-based learning for first order regression. ICML 2005: 193-200 - Yaakov Engel, Shie Mannor, Ron Meir:
Reinforcement learning with Gaussian processes. ICML 2005: 201-208 - Roberto Esposito, Lorenza Saitta:
Experimental comparison between bagging and Monte Carlo ensemble classification. ICML 2005: 209-216 - Thomas Finley, Thorsten Joachims:
Supervised clustering with support vector machines. ICML 2005: 217-224 - Holger Fröhlich, Jörg K. Wegner, Florian Sieker, Andreas Zell:
Optimal assignment kernels for attributed molecular graphs. ICML 2005: 225-232 - Pierre Geurts, Louis Wehenkel:
Closed-form dual perturb and combine for tree-based models. ICML 2005: 233-240 - Mark A. Girolami, Simon Rogers:
Hierarchic Bayesian models for kernel learning. ICML 2005: 241-248
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