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IJCAI
2007
15 years 8 months ago
Learning to Identify Unexpected Instances in the Test Set
Traditional classification involves building a classifier using labeled training examples from a set of predefined classes and then applying the classifier to classify test instan...
Xiaoli Li, Bing Liu, See-Kiong Ng
ECAI
2000
Springer
15 years 11 months ago
Similarity-based Approach to Relevance Learning
In several information retrieval (IR) systems there is a possibility for user feedback. Many machine learning methods have been proposed that learn from the feedback information in...
Rickard Cöster, Lars Asker
ILP
2004
Springer
16 years 5 days ago
Learning Ensembles of First-Order Clauses for Recall-Precision Curves: A Case Study in Biomedical Information Extraction
Many domains in the field of Inductive Logic Programming (ILP) involve highly unbalanced data. Our research has focused on Information Extraction (IE), a task that typically invol...
Mark Goadrich, Louis Oliphant, Jude W. Shavlik
PAMI
2011
14 years 9 months ago
Robust Object Tracking with Online Multiple Instance Learning
In this paper we address the problem of tracking an object in a video given its location in the first frame and no other information. Recently, a class of tracking techniques cal...
Boris Babenko, Ming-Hsuan Yang, Serge Belongie
IJAR
2010
113views more  IJAR 2010»
15 years 5 months ago
A geometric view on learning Bayesian network structures
We recall the basic idea of an algebraic approach to learning Bayesian network (BN) structures, namely to represent every BN structure by a certain (uniquely determined) vector, c...
Milan Studený, Jirí Vomlel, Raymond ...