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» Learning with the Set Covering Machine
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ICML
1994
IEEE
14 years 2 months ago
Efficient Algorithms for Minimizing Cross Validation Error
Model selection is important in many areas of supervised learning. Given a dataset and a set of models for predicting with that dataset, we must choose the model which is expected...
Andrew W. Moore, Mary S. Lee
ECML
2006
Springer
14 years 18 days ago
Cascade Evaluation of Clustering Algorithms
Abstract. This paper is about the evaluation of the results of clustering algorithms, and the comparison of such algorithms. We propose a new method based on the enrichment of a se...
Laurent Candillier, Isabelle Tellier, Fabien Torre...
FLAIRS
2000
13 years 12 months ago
Reasoning from Data Rather than Theory
Thecurrent frameworkfor constructing intelligent tutoring systems(ITS) is to use psychological/pedagogical theories of learning, and encode this knowledgeinto the tutor. However,t...
Joseph E. Beck, Beverly Park Woolf
ECTEL
2008
Springer
13 years 11 months ago
Immediate Elaborated Feedback Personalization in Online Assessment
Providing a student with feedback that is timely, most suitable and useful for her personality and the performed task is a challenging problem of online assessment within Web-based...
Ekaterina Vasilyeva, Paul De Bra, Mykola Pechenizk...
ICML
2010
IEEE
13 years 11 months ago
Tree-Guided Group Lasso for Multi-Task Regression with Structured Sparsity
We consider the problem of learning a sparse multi-task regression, where the structure in the outputs can be represented as a tree with leaf nodes as outputs and internal nodes a...
Seyoung Kim, Eric P. Xing