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ICML
2007
IEEE
15 years 10 months ago
Multi-task reinforcement learning: a hierarchical Bayesian approach
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
IUI
2006
ACM
15 years 3 months ago
Who's asking for help?: a Bayesian approach to intelligent assistance
Automated software customization is drawing increasing attention as a means to help users deal with the scope, complexity, potential intrusiveness, and ever-changing nature of mod...
Bowen Hui, Craig Boutilier
CLADE
2008
IEEE
15 years 3 months ago
SWARM: a scientific workflow for supporting bayesian approaches to improve metabolic models
With the exponential growth of complete genome sequences, the analysis of these sequences is becoming a powerful approach to build genome-scale metabolic models. These models can ...
Xinghua Shi, Rick Stevens
KBSE
2007
IEEE
15 years 3 months ago
Modeling bug report quality
Software developers spend a significant portion of their resources handling user-submitted bug reports. For software that is widely deployed, the number of bug reports typically ...
Pieter Hooimeijer, Westley Weimer
BMCBI
2004
177views more  BMCBI 2004»
14 years 9 months ago
Gapped alignment of protein sequence motifs through Monte Carlo optimization of a hidden Markov model
Background: Certain protein families are highly conserved across distantly related organisms and belong to large and functionally diverse superfamilies. The patterns of conservati...
Andrew F. Neuwald, Jun S. Liu