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GECCO
2007
Springer
143views Optimization» more  GECCO 2007»
14 years 2 months ago
Learning and exploiting knowledge in multi-agent task allocation problems
Imagine a group of cooperating agents attempting to allocate tasks amongst themselves without knowledge of their own capabilities. Over time, they develop a belief of their own sk...
Adam Campbell, Annie S. Wu
BMVC
2010
13 years 6 months ago
Label propagation in complex video sequences using semi-supervised learning
We propose a novel directed graphical model for label propagation in lengthy and complex video sequences. Given hand-labelled start and end frames of a video sequence, a variation...
Ignas Budvytis, Vijay Badrinarayanan, Roberto Cipo...
ICTAI
2010
IEEE
13 years 6 months ago
Combining Mixed Integer Programming and Supervised Learning for Fast Re-planning
We introduce a new plan repair method for problems cast as Mixed Integer Programs. In order to tackle the inherent complexity of these NP-hard problems, our approach relies on the ...
Emmanuel Rachelson, Ala Ben Abbes, Sebastien Dieme...
ICPR
2006
IEEE
14 years 9 months ago
Mixture of Support Vector Machines for HMM based Speech Recognition
Speech recognition is usually based on Hidden Markov Models (HMMs), which represent the temporal dynamics of speech very efficiently, and Gaussian mixture models, which do non-opt...
Sven E. Krüger, Martin Schafföner, Marce...
CORR
2011
Springer
178views Education» more  CORR 2011»
13 years 2 days ago
Online Learning: Stochastic and Constrained Adversaries
Learning theory has largely focused on two main learning scenarios. The first is the classical statistical setting where instances are drawn i.i.d. from a fixed distribution and...
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari