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» Formulating distance functions via the kernel trick
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AAAI
2010
13 years 9 months ago
Stability and Incentive Compatibility in a Kernel-Based Combinatorial Auction
We present the design and analysis of an approximately incentive-compatible combinatorial auction. In just a single run, the auction is able to extract enough value information fr...
Sébastien Lahaie
TIP
2011
164views more  TIP 2011»
13 years 2 months ago
Multiregion Image Segmentation by Parametric Kernel Graph Cuts
Abstract—The purpose of this study is to investigate multiregion graph cut image partitioning via kernel mapping of the image data. The image data is transformed implicitly by a ...
Mohamed Ben Salah, Amar Mitiche, Ismail Ben Ayed
JMLR
2006
150views more  JMLR 2006»
13 years 7 months ago
Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization
Support vector machines utilizing the 1-norm, typically set up as linear programs (Mangasarian, 2000; Bradley and Mangasarian, 1998), are formulated here as a completely unconstra...
Olvi L. Mangasarian
TKDE
2002
133views more  TKDE 2002»
13 years 7 months ago
Binary Rule Generation via Hamming Clustering
The generation of a set of rules underlying a classification problem is performed by applying a new algorithm, called Hamming Clustering (HC). It reconstructs the and-or expressio...
Marco Muselli, Diego Liberati
ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
15 years 18 days ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer