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» Generalization Bounds for Learning Kernels
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ALT
2010
Springer
13 years 11 months ago
Approximation Stability and Boosting
Stability has been explored to study the performance of learning algorithms in recent years and it has been shown that stability is sufficient for generalization and is sufficient ...
Wei Gao, Zhi-Hua Zhou
SIGIR
2008
ACM
13 years 9 months ago
Directly optimizing evaluation measures in learning to rank
One of the central issues in learning to rank for information retrieval is to develop algorithms that construct ranking models by directly optimizing evaluation measures used in i...
Jun Xu, Tie-Yan Liu, Min Lu, Hang Li, Wei-Ying Ma
ATAL
2006
Springer
14 years 1 months ago
A hierarchical approach to efficient reinforcement learning in deterministic domains
Factored representations, model-based learning, and hierarchies are well-studied techniques for improving the learning efficiency of reinforcement-learning algorithms in large-sca...
Carlos Diuk, Alexander L. Strehl, Michael L. Littm...
ICML
2005
IEEE
14 years 10 months ago
Using additive expert ensembles to cope with concept drift
We consider online learning where the target concept can change over time. Previous work on expert prediction algorithms has bounded the worst-case performance on any subsequence ...
Jeremy Z. Kolter, Marcus A. Maloof
ICML
2004
IEEE
14 years 10 months ago
Approximate inference by Markov chains on union spaces
A standard method for approximating averages in probabilistic models is to construct a Markov chain in the product space of the random variables with the desired equilibrium distr...
Max Welling, Michal Rosen-Zvi, Yee Whye Teh