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JMLR
2006
169views more  JMLR 2006»
13 years 9 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
MP
2006
142views more  MP 2006»
13 years 9 months ago
Exploring the Relationship Between Max-Cut and Stable Set Relaxations
The max-cut and stable set problems are two fundamental NP-hard problems in combinatorial optimization. It has been known for a long time that any instance of the stable set probl...
Monia Giandomenico, Adam N. Letchford
NPL
2006
172views more  NPL 2006»
13 years 9 months ago
Adapting RBF Neural Networks to Multi-Instance Learning
In multi-instance learning, the training examples are bags composed of instances without labels, and the task is to predict the labels of unseen bags through analyzing the training...
Min-Ling Zhang, Zhi-Hua Zhou
PAMI
2006
230views more  PAMI 2006»
13 years 9 months ago
Shape Registration in Implicit Spaces Using Information Theory and Free Form Deformations
We present a novel variational and statistical approach for shape registration. Shapes of interest are implicitly embedded in a higher dimensional space of distance transforms. In...
Xiaolei Huang, Nikos Paragios, Dimitris N. Metaxas
SIAMSC
2008
131views more  SIAMSC 2008»
13 years 9 months ago
Fast Monte Carlo Simulation Methods for Biological Reaction-Diffusion Systems in Solution and on Surfaces
Many important physiological processes operate at time and space scales far beyond those accessible to atom-realistic simulations, and yet discrete stochastic rather than continuum...
Rex A. Kerr, Thomas M. Bartol, Boris Kaminsky, Mar...
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