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ICML
2006
IEEE
16 years 7 months ago
An analytic solution to discrete Bayesian reinforcement learning
Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms co...
Pascal Poupart, Nikos A. Vlassis, Jesse Hoey, Kevi...
ICML
2005
IEEE
16 years 7 months ago
Beyond the point cloud: from transductive to semi-supervised learning
Due to its occurrence in engineering domains and implications for natural learning, the problem of utilizing unlabeled data is attracting increasing attention in machine learning....
Vikas Sindhwani, Partha Niyogi, Mikhail Belkin
ICML
1999
IEEE
16 years 7 months ago
Using Reinforcement Learning to Spider the Web Efficiently
Consider the task of exploring the Web in order to find pages of a particular kind or on a particular topic. This task arises in the construction of search engines and Web knowled...
Jason Rennie, Andrew McCallum
GECCO
2010
Springer
157views Optimization» more  GECCO 2010»
15 years 10 months ago
Speeding up the evaluation of evolutionary learning systems using GPGPUs
In this paper we introduce a method for computing fitness in evolutionary learning systems based on NVIDIA’s massive parallel technology using the CUDA library. Both the match ...
María A. Franco, Natalio Krasnogor, Jaume B...
184
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AAAI
2008
15 years 9 months ago
The PELA Architecture: Integrating Planning and Learning to Improve Execution
Building architectures for autonomous rational behavior requires the integration of several AI components, such as planning, learning and execution monitoring. In most cases, the ...
Sergio Jiménez, Fernando Fernández, ...