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» Kernelizations for Parameterized Counting Problems
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ICASSP
2011
IEEE
12 years 11 months ago
Adaptive N-normalization for enhancing music similarity
The N-Normalization is an efficient method for normalizing a given similarity computed among multimedia objects. It can be considered for clustering and kernel enhancement. Howev...
Mathieu Lagrange, George Tzanetakis
ICML
2009
IEEE
14 years 8 months ago
Partial order embedding with multiple kernels
We consider the problem of embedding arbitrary objects (e.g., images, audio, documents) into Euclidean space subject to a partial order over pairwise distances. Partial order cons...
Brian McFee, Gert R. G. Lanckriet
ISAAC
2009
Springer
109views Algorithms» more  ISAAC 2009»
14 years 2 months ago
A Linear Vertex Kernel for Maximum Internal Spanning Tree
We present an algorithm that for any graph G and integer k ≥ 0 in time polynomial in the size of G either nds a spanning tree with at least k internal vertices, or outputs a ne...
Fedor V. Fomin, Serge Gaspers, Saket Saurabh, St&e...
JMLR
2012
11 years 10 months ago
Metric and Kernel Learning Using a Linear Transformation
Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
Prateek Jain, Brian Kulis, Jason V. Davis, Inderji...
FSTTCS
2010
Springer
13 years 5 months ago
The effect of girth on the kernelization complexity of Connected Dominating Set
In the Connected Dominating Set problem we are given as input a graph G and a positive integer k, and are asked if there is a set S of at most k vertices of G such that S is a dom...
Neeldhara Misra, Geevarghese Philip, Venkatesh Ram...