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NIPS
2007
15 years 6 months ago
Kernels on Attributed Pointsets with Applications
This paper introduces kernels on attributed pointsets, which are sets of vectors embedded in an euclidean space. The embedding gives the notion of neighborhood, which is used to d...
Mehul Parsana, Sourangshu Bhattacharya, Chiru Bhat...
ICML
2004
IEEE
15 years 10 months ago
Learning a kernel matrix for nonlinear dimensionality reduction
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul
CORR
2012
Springer
208views Education» more  CORR 2012»
14 years 1 months ago
Ensembles of Kernel Predictors
This paper examines the problem of learning with a finite and possibly large set of p base kernels. It presents a theoretical and empirical analysis of an approach addressing thi...
Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
JUCS
2010
135views more  JUCS 2010»
15 years 3 months ago
Static Analysis of the XEN Kernel using Frama-C
: In this paper, we describe the static analysis of the XEN 3.0.3 hypervisor using the Frama-C static analysis tool.
Armand Puccetti
130
Voted
ICPR
2002
IEEE
15 years 10 months ago
A Large Scale Clustering Scheme for Kernel K-Means
Kernel functions can be viewed as a non-linear transformation that increases the separability of the input data by mapping them to a new high dimensional space. The incorporation ...
Rong Zhang, Alexander I. Rudnicky