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» Reinforcement Learning Estimation of Distribution Algorithm
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CEC
2010
IEEE
15 years 3 months ago
A novel memetic algorithm for constrained optimization
In this paper, we present a memetic algorithm with novel local optimizer hybridization strategy for constrained optimization. The developed MA consists of multiple cycles. In each ...
Jianyong Sun, Jonathan M. Garibaldi
ICCV
2007
IEEE
16 years 4 months ago
Graph Based Discriminative Learning for Robust and Efficient Object Tracking
Object tracking is viewed as a two-class 'one-versusrest' classification problem, in which the sample distribution of the target is approximately Gaussian while the back...
Xiaoqin Zhang, Weiming Hu, Stephen J. Maybank, Xi ...
ICML
2009
IEEE
15 years 9 months ago
Using fast weights to improve persistent contrastive divergence
The most commonly used learning algorithm for restricted Boltzmann machines is contrastive divergence which starts a Markov chain at a data point and runs the chain for only a few...
Tijmen Tieleman, Geoffrey E. Hinton

Publication
173views
14 years 1 months ago
Max-Flow Segmentation of the Left Ventricle by Recovering Subject-Specific Distributions via a Bound of the Bhattacharyya Measur
This study investigates fast detection of the left ventricle (LV) endo- and epicardium boundaries in a cardiac magnetic resonance (MR) sequence following the optimization of two or...
Ismail Ben Ayed, Hua-mei Chen, Kumaradevan Punitha...
EPIA
2003
Springer
15 years 7 months ago
Adaptation to Drifting Concepts
Most of supervised learning algorithms assume the stability of the target concept over time. Nevertheless in many real-user modeling systems, where the data is collected over an ex...
Gladys Castillo, João Gama, Pedro Medas