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KDD
2002
ACM
171views Data Mining» more  KDD 2002»
16 years 6 days ago
Mining complex models from arbitrarily large databases in constant time
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
Geoff Hulten, Pedro Domingos
CVPR
2010
IEEE
15 years 7 months ago
Data Fusion through Cross-modality Metric Learning using Similarity-Sensitive Hashing
Visual understanding is often based on measuring similarity between observations. Learning similarities specific to a certain perception task from a set of examples has been show...
Michael Bronstein, Alexander Bronstein, Nikos Para...
PR
2008
145views more  PR 2008»
14 years 11 months ago
Probabilistic suffix models for API sequence analysis of Windows XP applications
Given the pervasive nature of malicious mobile code (viruses, worms, etc.), developing statistical/structural models of code execution is of considerable importance. We investigat...
Geoffrey Mazeroff, Jens Gregor, Michael G. Thomaso...
PR
2008
154views more  PR 2008»
14 years 11 months ago
Data-driven decomposition for multi-class classification
This paper presents a new study on a method of designing a multi-class classifier: Data-driven Error Correcting Output Coding (DECOC). DECOC is based on the principle of Error Cor...
Jie Zhou, Hanchuan Peng, Ching Y. Suen
PR
2006
80views more  PR 2006»
14 years 11 months ago
Neighborhood size selection in the k-nearest-neighbor rule using statistical confidence
The k-nearest-neighbor rule is one of the most attractive pattern classification algorithms. In practice, the choice of k is determined by the cross-validation method. In this wor...
Jigang Wang, Predrag Neskovic, Leon N. Cooper