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» An Instance Selection Approach to Multiple Instance Learning
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IAT
2005
IEEE
15 years 3 months ago
Self-Organizing Cognitive Agents and Reinforcement Learning in Multi-Agent Environment
This paper presents a self-organizing cognitive architecture, known as TD-FALCON, that learns to function through its interaction with the environment. TD-FALCON learns the value ...
Ah-Hwee Tan, Dan Xiao
RECOMB
1997
Springer
15 years 2 months ago
A branch-and-cut algorithm for multiple sequence alignment
Multiple sequence alignment is an important problem in computational biology. We study the Maximum Trace formulation introduced by Kececioglu [?]. We first phrase the problem in ...
Knut Reinert, Hans-Peter Lenhof, Petra Mutzel, Kur...
AAAI
2010
14 years 11 months ago
Automated Program Debugging Via Multiple Predicate Switching
In a previous paper, Liu argued for the importance of establishing a precise theoretical foundation for program debugging from first principles. In this paper, we present a first ...
Yongmei Liu, Bing Li
ICML
2007
IEEE
15 years 10 months ago
Learning a meta-level prior for feature relevance from multiple related tasks
In many prediction tasks, selecting relevant features is essential for achieving good generalization performance. Most feature selection algorithms consider all features to be a p...
Su-In Lee, Vassil Chatalbashev, David Vickrey, Dap...
IRI
2008
IEEE
15 years 4 months ago
Robust integration of multiple information sources by view completion
There are many applications where multiple data sources, each with its own features, are integrated in order to perform an inference task in an optimal way. Researchers have shown...
Shankara B. Subramanya, Baoxin Li, Huan Liu