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NIPS
1998
15 years 5 months ago
Learning Nonlinear Dynamical Systems Using an EM Algorithm
The Expectation Maximization EM algorithm is an iterative procedure for maximum likelihood parameter estimation from data sets with missing or hidden variables 2 . It has been app...
Zoubin Ghahramani, Sam T. Roweis
140
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BMCBI
2010
133views more  BMCBI 2010»
15 years 3 months ago
Improving de novo sequence assembly using machine learning and comparative genomics for overlap correction
Background: With the rapid expansion of DNA sequencing databases, it is now feasible to identify relevant information from prior sequencing projects and completed genomes and appl...
Lance E. Palmer, Mathäus Dejori, Randall A. B...
148
Voted
JAIR
2008
157views more  JAIR 2008»
15 years 3 months ago
Learning to Reach Agreement in a Continuous Ultimatum Game
It is well-known that acting in an individually rational manner, according to the principles of classical game theory, may lead to sub-optimal solutions in a class of problems nam...
Steven de Jong, Simon Uyttendaele, Karl Tuyls
138
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JUCS
2008
118views more  JUCS 2008»
15 years 3 months ago
Enhancements of Meeting Information Management and Application for Knowledge Access and Learning Activities
: Communication processes have become increasingly important in modern working life. Organizations invest a surprisingly high amount of financial resources and employee work time i...
Christian Gütl
RAS
2008
80views more  RAS 2008»
15 years 3 months ago
Motion design and learning of autonomous robots based on primitives and heuristic cost-to-go
The task of trajectory design of autonomous vehicles is typically two-fold. First, it needs to take into account the intrinsic dynamics of the vehicle, which are sometimes termed ...
Keyong Li, Raffaello D'Andrea