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» Hierarchical Unsupervised Learning
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BMCBI
2006
216views more  BMCBI 2006»
15 years 21 days ago
Machine learning approaches to supporting the identification of photoreceptor-enriched genes based on expression data
Background: Retinal photoreceptors are highly specialised cells, which detect light and are central to mammalian vision. Many retinal diseases occur as a result of inherited dysfu...
Haiying Wang, Huiru Zheng, David Simpson, Francisc...
97
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ICML
2006
IEEE
16 years 1 months ago
Collaborative ordinal regression
Ordinal regression has become an effective way of learning user preferences, but most of research only focuses on single regression problem. In this paper we introduce collaborati...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
121
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IROS
2008
IEEE
141views Robotics» more  IROS 2008»
15 years 7 months ago
Active sensing based dynamical object feature extraction
— This paper presents a method to autonomously extract object features that describe their dynamics from active sensing experiences. The model is composed of a dynamics learning ...
Shun Nishide, Tetsuya Ogata, Ryunosuke Yokoya, Jun...
AIIDE
2009
15 years 1 months ago
Examining Extended Dynamic Scripting in a Tactical Game Framework
Dynamic scripting is a reinforcement learning algorithm designed specifically to learn appropriate tactics for an agent in a modern computer game, such as Neverwinter Nights. This...
Jeremy Ludwig, Arthur Farley
113
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GECCO
2008
Springer
232views Optimization» more  GECCO 2008»
15 years 1 months ago
An efficient SVM-GA feature selection model for large healthcare databases
This paper presents an efficient hybrid feature selection model based on Support Vector Machine (SVM) and Genetic Algorithm (GA) for large healthcare databases. Even though SVM an...
Rick Chow, Wei Zhong, Michael Blackmon, Richard St...