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» Learning and Inference with Constraints
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JMLR
2012
13 years 9 months ago
Structured Output Learning with High Order Loss Functions
Often when modeling structured domains, it is desirable to leverage information that is not naturally expressed as simply a label. Examples include knowledge about the evaluation ...
Daniel Tarlow, Richard S. Zemel
CVPR
2005
IEEE
16 years 8 months ago
Fields of Experts: A Framework for Learning Image Priors
We develop a framework for learning generic, expressive image priors that capture the statistics of natural scenes and can be used for a variety of machine vision tasks. The appro...
Stefan Roth, Michael J. Black
ICML
2007
IEEE
16 years 7 months ago
The matrix stick-breaking process for flexible multi-task learning
In multi-task learning our goal is to design regression or classification models for each of the tasks and appropriately share information between tasks. A Dirichlet process (DP) ...
Ya Xue, David B. Dunson, Lawrence Carin
AICCSA
2006
IEEE
133views Hardware» more  AICCSA 2006»
16 years 17 days ago
Learning acyclic rules based on Chaining Genetic Programming
Multi-class problem is the class of problems having more than one classes in the data set. Bayesian Network (BN) is a well-known algorithm handling the multi-class problem and is ...
Wing-Ho Shum, Kwong-Sak Leung, Man Leung Wong
AIMSA
2004
Springer
15 years 12 months ago
PubMiner: Machine Learning-Based Text Mining System for Biomedical Information Mining
PubMiner, an intelligent machine learning based text mining system for mining biological information from the literature is introduced. PubMiner utilize natural language processing...
Jae-Hong Eom, Byoung-Tak Zhang