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» Learning When to Use Lazy Learning in Constraint Solving
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NIPS
2007
13 years 9 months ago
Multi-Task Learning via Conic Programming
When we have several related tasks, solving them simultaneously is shown to be more effective than solving them individually. This approach is called multi-task learning (MTL) and...
Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama, ...
COMSIS
2006
129views more  COMSIS 2006»
13 years 7 months ago
Constraint-Based Knowledge Representation for Individualized Instruction
Traditional knowledge representations were developed to encode complete, explicit and executable programs, a goal that makes them less than ideal for representing the incomplete an...
Stellan Ohlsson, Antonija Mitrovic
AMAI
1999
Springer
13 years 7 months ago
Maintenance scheduling problems as benchmarks for constraint algorithms
The paper focuses on evaluating constraint satisfaction search algorithms on application based random problem instances. The application we use is a well-studied problem in the el...
Daniel Frost, Rina Dechter
CVPR
2010
IEEE
14 years 21 days ago
Anatomical Parts-Based Regression Using Non-Negative Matrix Factorization
Non-negative matrix factorization (NMF) is an excellent tool for unsupervised parts-based learning, but proves to be ineffective when parts of a whole follow a specific pattern. ...
Swapna Joshi, Karthikeyan Shanmugavadivel, B.S. Ma...
GECCO
2008
Springer
126views Optimization» more  GECCO 2008»
13 years 8 months ago
Swarm intelligence in e-learning: a learning object sequencing agent based on competencies
In e-learning initiatives content creators are usually required to arrange a set of learning resources in order to present them in a comprehensive way to the learner. Course mater...
Luis de Marcos, José-Javier Martínez...