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IJCAI
2007
13 years 9 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
CVPR
2009
IEEE
15 years 2 months ago
A Min-Max Framework of Cascaded Classifier with Multiple Instance Learning for Computer Aided Diagnosis
The computer aided diagnosis (CAD) problems of detecting potentially diseased structures from medical images are typically distinguished by the following challenging characterist...
Dijia Wu (Rensselaer Polytechnic Institute), Jinbo...
CSCLP
2005
Springer
14 years 1 months ago
On Generators of Random Quasigroup Problems
Problems that can be sampled randomly are a good source of test suites for comparing quality of constraint satisfaction techniques. Quasigroup problems are representatives of struc...
Roman Barták
JAIR
2000
123views more  JAIR 2000»
13 years 7 months ago
Backbone Fragility and the Local Search Cost Peak
The local search algorithm WSat is one of the most successful algorithms for solving the satisfiability (SAT) problem. It is notably effective at solving hard Random 3-SAT instanc...
Josh Singer, Ian P. Gent, Alan Smaill
IJCAI
1997
13 years 9 months ago
Automatic Generation of Heuristics for Scheduling
This paper presents a technique, called GENH, that automatically generates search heuristics for scheduling problems. The impetus for developing this technique is the growing cons...
Robert A. Morris, John L. Bresina, Stuart M. Rodge...