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» Classifier Combining Rules Under Independence Assumptions
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JMLR
2006
123views more  JMLR 2006»
13 years 6 months ago
Adaptive Prototype Learning Algorithms: Theoretical and Experimental Studies
In this paper, we propose a number of adaptive prototype learning (APL) algorithms. They employ the same algorithmic scheme to determine the number and location of prototypes, but...
Fu Chang, Chin-Chin Lin, Chi-Jen Lu
TIT
2010
118views Education» more  TIT 2010»
13 years 1 months ago
Joint sampling distribution between actual and estimated classification errors for linear discriminant analysis
Error estimation must be used to find the accuracy of a designed classifier, an issue that is critical in biomarker discovery for disease diagnosis and prognosis in genomics and p...
Amin Zollanvari, Ulisses Braga-Neto, Edward R. Dou...
ASIACRYPT
2011
Springer
12 years 6 months ago
Noiseless Database Privacy
Differential Privacy (DP) has emerged as a formal, flexible framework for privacy protection, with a guarantee that is agnostic to auxiliary information and that admits simple ru...
Raghav Bhaskar, Abhishek Bhowmick, Vipul Goyal, Sr...
CVPR
2004
IEEE
14 years 8 months ago
Gibbs Likelihoods for Bayesian Tracking
Bayesian methods for visual tracking model the likelihood of image measurements conditioned on a tracking hypothesis. Image measurements may, for example, correspond to various fi...
Stefan Roth, Leonid Sigal, Michael J. Black
WABI
2009
Springer
127views Bioinformatics» more  WABI 2009»
14 years 1 months ago
Constructing Majority-Rule Supertrees
Background: Supertree methods combine the phylogenetic information from multiple partially-overlapping trees into a larger phylogenetic tree called a supertree. Several supertree ...
Jianrong Dong, David Fernández-Baca, Fred R...