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ICASSP
2010
IEEE
13 years 10 months ago
Hierarchical Gaussian Mixture Model
Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...
Vincent Garcia, Frank Nielsen, Richard Nock
CORR
2006
Springer
153views Education» more  CORR 2006»
13 years 10 months ago
A distributed approximation algorithm for the minimum degree minimum weight spanning trees
Fischer proposes in [4] a sequential algorithm to compute a minimum weight spanning tree of maximum degree at most b + logb n in time O n4+1/ln b for any constant b > 1, where ...
Christian Lavault, Mario Valencia-Pabon
EOR
2007
159views more  EOR 2007»
13 years 10 months ago
Solving the semi-desirable facility location problem using bi-objective particle swarm
In this paper, a new model for the semi-obnoxious facility location problem is introduced. The new model is composed of a weighted minisum function to represent the transportation...
Haluk Yapicioglu, Alice E. Smith, Gerry V. Dozier
AMAI
2004
Springer
13 years 10 months ago
Logical Preference Representation and Combinatorial Vote
We introduce the notion of combinatorial vote, where a group of agents (or voters) is supposed to express preferences and come to a common decision concerning a set of non-independ...
Jérôme Lang
AROBOTS
2002
91views more  AROBOTS 2002»
13 years 10 months ago
Fast, On-Line Learning of Globally Consistent Maps
To navigate in unknown environments, mobile robots require the ability to build their own maps. A major problem for robot map building is that odometry-based dead reckoning cannot ...
Tom Duckett, Stephen Marsland, Jonathan Shapiro