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» Kernels for Global Constraints
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NIPS
2004
13 years 11 months ago
Maximum Margin Clustering
We propose a new method for clustering based on finding maximum margin hyperplanes through data. By reformulating the problem in terms of the implied equivalence relation matrix, ...
Linli Xu, James Neufeld, Bryce Larson, Dale Schuur...
CCR
2010
156views more  CCR 2010»
13 years 9 months ago
Evolvable network architectures: what can we learn from biology?
There is significant research interest recently to understand the evolution of the current Internet, as well as to design clean-slate Future Internet architectures. Clearly, even ...
Constantine Dovrolis, J. Todd Streelman
CSDA
2007
126views more  CSDA 2007»
13 years 9 months ago
A consistent nonparametric Bayesian procedure for estimating autoregressive conditional densities
This article proposes a Bayesian infinite mixture model for the estimation of the conditional density of an ergodic time series. A nonparametric prior on the conditional density ...
Yongqiang Tang, Subhashis Ghosal
DEBU
2007
131views more  DEBU 2007»
13 years 9 months ago
Future Trends in Secure Chip Data Management
Secure chips, e.g. present in smart cards, TPM, USB dongles are now ubiquitous in applications with strong security requirements. Secure chips host personal data that must be care...
Nicolas Anciaux, Luc Bouganim, Philippe Pucheral
IVC
2007
176views more  IVC 2007»
13 years 9 months ago
Kernel-based distance metric learning for content-based image retrieval
ct 8 For a specific set of features chosen for representing images, the performance of a content-based image retrieval (CBIR) system 9 depends critically on the similarity or diss...
Hong Chang, Dit-Yan Yeung