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JACM
2006
99views more  JACM 2006»
13 years 7 months ago
Finding a maximum likelihood tree is hard
Abstract. Maximum likelihood (ML) is an increasingly popular optimality criterion for selecting evolutionary trees [Felsenstein 1981]. Finding optimal ML trees appears to be a very...
Benny Chor, Tamir Tuller
CVIU
2007
154views more  CVIU 2007»
13 years 7 months ago
Smart particle filtering for high-dimensional tracking
Tracking articulated structures like a hand or body within a reasonable time is challenging because of the high dimensionality of the state space. Recently, a new optimization met...
Matthieu Bray, Esther Koller-Meier, Luc J. Van Goo...
JSAC
2008
140views more  JSAC 2008»
13 years 7 months ago
Optimality and Complexity of Pure Nash Equilibria in the Coverage Game
In this paper, we investigate the coverage problem in wireless sensor networks using a game theory method. We assume that nodes are randomly scattered in a sensor field and the goa...
Xin Ai, Vikram Srinivasan, Chen-Khong Tham
JUCS
2008
115views more  JUCS 2008»
13 years 7 months ago
Capturing Interaction Requirements in a Model Transformation Technology Based on MDA
: Currently, many models are used to capture functional software requirements. However, the Software Engineering community has faded interaction requirements into the background, d...
José Ignacio Panach, Sergio España, ...
JMLR
2006
108views more  JMLR 2006»
13 years 7 months ago
The Interplay of Optimization and Machine Learning Research
The fields of machine learning and mathematical programming are increasingly intertwined. Optimization problems lie at the heart of most machine learning approaches. The Special T...
Kristin P. Bennett, Emilio Parrado-Hernánde...
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