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» Reinforcement Learning with the Use of Costly Features
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ECML
2004
Springer
14 years 3 months ago
Experiments in Value Function Approximation with Sparse Support Vector Regression
Abstract. We present first experiments using Support Vector Regression as function approximator for an on-line, sarsa-like reinforcement learner. To overcome the batch nature of S...
Tobias Jung, Thomas Uthmann
INFOCOM
2005
IEEE
14 years 3 months ago
A performance vs. cost framework for evaluating DHT design tradeoffs under churn
Abstract— Protocols for distributed hash tables (DHTs) incorporate features to achieve low latency for lookup requests in the face of churn, continuous changes in membership. The...
Jinyang Li, Jeremy Stribling, Robert Morris, M. Fr...
NIPS
1993
13 years 11 months ago
Using Local Trajectory Optimizers to Speed Up Global Optimization in Dynamic Programming
Dynamic programming provides a methodology to develop planners and controllers for nonlinear systems. However, general dynamic programming is computationally intractable. We have ...
Christopher G. Atkeson
COLING
2008
13 years 11 months ago
Extractive Summarization Using Supervised and Semi-Supervised Learning
It is difficult to identify sentence importance from a single point of view. In this paper, we propose a learning-based approach to combine various sentence features. They are cat...
Kam-Fai Wong, Mingli Wu, Wenjie Li
ICIP
2010
IEEE
13 years 8 months ago
Multimodal template matching based on gradient and mutual information using scale-space
This paper presents the combined use of gradient and mutual information for infrared and intensity templates matching. We propose to joint: (i) feature matching in a multiresoluti...
Fernando Barrera, Felipe Lumbreras, Angel Domingo ...