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» Using Problems to Learn Service-Oriented Computing
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FLAIRS
2004
15 years 3 months ago
Developing Task Specific Sensing Strategies Using Reinforcement Learning
Robots that can adapt and perform multiple tasks promise to be a powerful tool with many applications. In order to achieve such robots, control systems have to be constructed that...
Srividhya Rajendran, Manfred Huber
ECAI
2008
Springer
15 years 4 months ago
Reinforcement Learning with the Use of Costly Features
In many practical reinforcement learning problems, the state space is too large to permit an exact representation of the value function, much less the time required to compute it. ...
Robby Goetschalckx, Scott Sanner, Kurt Driessens
166
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CVPR
2012
IEEE
13 years 4 months ago
Unsupervised feature learning framework for no-reference image quality assessment
In this paper, we present an efficient general-purpose objective no-reference (NR) image quality assessment (IQA) framework based on unsupervised feature learning. The goal is to...
Peng Ye, Jayant Kumar, Le Kang, David S. Doermann
ECML
2004
Springer
15 years 6 months ago
Efficient Hyperkernel Learning Using Second-Order Cone Programming
The kernel function plays a central role in kernel methods. Most existing methods can only adapt the kernel parameters or the kernel matrix based on empirical data. Recently, Ong e...
Ivor W. Tsang, James T. Kwok
132
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ISNN
2005
Springer
15 years 8 months ago
A Learning Framework for Blind Source Separation Using Generalized Eigenvalues
This paper presents a learning framework for blind source separation (BSS), in which the BSS is formulated as generalized Eigenvalue (GE) problem. Compared to the typical informati...
Hailin Liu, Yiu-ming Cheung