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IJCAI
2007
15 years 5 months ago
Using Linear Programming for Bayesian Exploration in Markov Decision Processes
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
Pablo Samuel Castro, Doina Precup
NIPS
2007
15 years 5 months ago
Multi-task Gaussian Process Prediction
In this paper we investigate multi-task learning in the context of Gaussian Processes (GP). We propose a model that learns a shared covariance function on input-dependent features...
Edwin V. Bonilla, Kian Ming Chai, Christopher K. I...
151
Voted
ICWS
2004
IEEE
15 years 5 months ago
Dynamic Workflow Composition using Markov Decision Processes
The advent of Web services has made automated workflow composition relevant to Web based applications. One technique that has received some attention, for automatically composing ...
Prashant Doshi, Richard Goodwin, Rama Akkiraju, Ku...
SIGMOD
2002
ACM
137views Database» more  SIGMOD 2002»
15 years 3 months ago
Partial results for online query processing
Traditional query processors generate full, accurate query results, either in batch or in pipelined fashion. We argue that this strict model is too rigid for exploratory queries o...
Vijayshankar Raman, Joseph M. Hellerstein
JMLR
2010
141views more  JMLR 2010»
14 years 10 months ago
Hierarchical Gaussian Process Regression
We address an approximation method for Gaussian process (GP) regression, where we approximate covariance by a block matrix such that diagonal blocks are calculated exactly while o...
Sunho Park, Seungjin Choi