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74
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ATAL
2006
Springer
15 years 1 months ago
Probabilistic policy reuse in a reinforcement learning agent
We contribute Policy Reuse as a technique to improve a reinforcement learning agent with guidance from past learned similar policies. Our method relies on using the past policies ...
Fernando Fernández, Manuela M. Veloso
74
Voted
STOC
2003
ACM
122views Algorithms» more  STOC 2003»
15 years 10 months ago
Learning juntas
We consider a fundamental problem in computational learning theory: learning an arbitrary Boolean function which depends on an unknown set of k out of n Boolean variables. We give...
Elchanan Mossel, Ryan O'Donnell, Rocco A. Servedio
BMCBI
2008
173views more  BMCBI 2008»
14 years 9 months ago
Improved machine learning method for analysis of gas phase chemistry of peptides
Background: Accurate peptide identification is important to high-throughput proteomics analyses that use mass spectrometry. Search programs compare fragmentation spectra (MS/MS) o...
Allison Gehrke, Shaojun Sun, Lukasz A. Kurgan, Nat...
99
Voted
ATAL
2010
Springer
14 years 10 months ago
PAC-MDP learning with knowledge-based admissible models
PAC-MDP algorithms approach the exploration-exploitation problem of reinforcement learning agents in an effective way which guarantees that with high probability, the algorithm pe...
Marek Grzes, Daniel Kudenko
KDD
2008
ACM
183views Data Mining» more  KDD 2008»
15 years 10 months ago
De-duping URLs via rewrite rules
A large fraction of the URLs on the web contain duplicate (or near-duplicate) content. De-duping URLs is an extremely important problem for search engines, since all the principal...
Anirban Dasgupta, Ravi Kumar, Amit Sasturkar