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» Optimization with Extremal Dynamics
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ICPR
2008
IEEE
16 years 17 days ago
Exploiting qualitative domain knowledge for learning Bayesian network parameters with incomplete data
When a large amount of data are missing, or when multiple hidden nodes exist, learning parameters in Bayesian networks (BNs) becomes extremely difficult. This paper presents a lea...
Qiang Ji, Wenhui Liao
ICML
2008
IEEE
16 years 5 days ago
A decoupled approach to exemplar-based unsupervised learning
A recent trend in exemplar based unsupervised learning is to formulate the learning problem as a convex optimization problem. Convexity is achieved by restricting the set of possi...
Gökhan H. Bakir, Sebastian Nowozin
CADE
2007
Springer
15 years 11 months ago
An Incremental Technique for Automata-Based Decision Procedures
Abstract. Automata-based decision procedures commonly achieve optimal complexity bounds. However, in practice, they are often outperformed by sub-optimal (but more local-search bas...
David Toman, Gulay Ünel
ISLPED
2003
ACM
96views Hardware» more  ISLPED 2003»
15 years 4 months ago
Effective graph theoretic techniques for the generalized low power binding problem
This paper proposes two very fast graph theoretic heuristics for the low power binding problem given fixed number of resources and multiple architectures for the resources. First...
Azadeh Davoodi, Ankur Srivastava
IFIP7
2001
Springer
137views Optimization» more  IFIP7 2001»
15 years 3 months ago
Data Mining via Support Vector Machines
Support vector machines (SVMs) have played a key role in broad classes of problems arising in various fields. Much more recently, SVMs have become the tool of choice for problems...
Olvi L. Mangasarian