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» Reformulating Constraint Models Using Input Data
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AAAI
1993
14 years 11 months ago
Scientific Model-Building as Search in Matrix Spaces
Many reported discovery systems build discrete models of hidden structure, properties, or processes in the diverse fields of biology, chemistry, and physics. We show that the sear...
Raúl E. Valdés-Pérez, Jan M. ...
GECCO
2009
Springer
131views Optimization» more  GECCO 2009»
14 years 7 months ago
A multi-objective approach to data sharing with privacy constraints and preference based objectives
Public data sharing is utilized in a number of businesses to facilitate the exchange of information. Privacy constraints are usually enforced to prevent unwanted inference of info...
Rinku Dewri, Darrell Whitley, Indrajit Ray, Indrak...
76
Voted
CORR
2012
Springer
187views Education» more  CORR 2012»
13 years 5 months ago
Sequential Inference for Latent Force Models
Latent force models (LFMs) are hybrid models combining mechanistic principles with non-parametric components. In this article, we shall show how LFMs can be equivalently formulate...
Jouni Hartikainen, Simo Särkkä
95
Voted
ISVC
2010
Springer
14 years 8 months ago
Automatic Learning of Gesture Recognition Model Using SOM and SVM
In this paper, we propose an automatic learning method for gesture recognition. We combine two different pattern recognition techniques: the SelfOrganizing Map (SOM) and Support Ve...
Masaki Oshita, Takefumi Matsunaga
ECML
2006
Springer
15 years 1 months ago
Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
Corneliu Henegar, Karine Clément, Jean-Dani...