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» Classifier Combining Rules Under Independence Assumptions
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JMLR
2006
123views more  JMLR 2006»
14 years 9 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»
14 years 4 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
13 years 9 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
15 years 11 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»
15 years 4 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...