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» Self Bounding Learning Algorithms
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STOC
2005
ACM
84views Algorithms» more  STOC 2005»
14 years 10 months ago
Learning nonsingular phylogenies and hidden Markov models
In this paper, we study the problem of learning phylogenies and hidden Markov models. We call the Markov model nonsingular if all transtion matrices have determinants bounded away...
Elchanan Mossel, Sébastien Roch
KES
1998
Springer
14 years 1 months ago
An acquisition of the relation between vision and action using self-organizing map and reinforcement learning
An agent must acquire internal representation appropriate for its task, environment, sensors. As a learning algorithm, reinforcement learning is often utilized to acquire the rela...
Kazunori Terada, Hideaki Takeda, Toyoaki Nishida
ATAL
2010
Springer
13 years 10 months ago
Self-organization for coordinating decentralized reinforcement learning
Decentralized reinforcement learning (DRL) has been applied to a number of distributed applications. However, one of the main challenges faced by DRL is its convergence. Previous ...
Chongjie Zhang, Victor R. Lesser, Sherief Abdallah
ALT
2006
Springer
14 years 6 months ago
Unsupervised Slow Subspace-Learning from Stationary Processes
Abstract. We propose a method of unsupervised learning from stationary, vector-valued processes. A low-dimensional subspace is selected on the basis of a criterion which rewards da...
Andreas Maurer
CVPR
2006
IEEE
14 years 3 months ago
Learning Non-Metric Partial Similarity Based on Maximal Margin Criterion
The performance of many computer vision and machine learning algorithms critically depends on the quality of the similarity measure defined over the feature space. Previous works...
Xiaoyang Tan, Songcan Chen, Jun Li, Zhi-Hua Zhou