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ICML
2005
IEEE
16 years 4 months ago
Active learning for Hidden Markov Models: objective functions and algorithms
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
Brigham Anderson, Andrew Moore
SIBGRAPI
2006
IEEE
15 years 9 months ago
Actively Illuminated Objects using Graph-Cuts
This paper addresses the problem of foreground extraction using active illumination and graph-cut optimization. Our approach starts by detecting image regions that are likely to b...
Asla Medeiros Sá, Marcelo Bernardes Vieira,...
IMCSIT
2010
15 years 1 months ago
PSO based modeling of Takagi-Sugeno fuzzy motion controller for dynamic object tracking with mobile platform
Modeling of optimized motion controller is one of the interesting problems in the context of behavior based mobile robotics. Behavior based mobile robots should have an ideal contr...
Meenakshi Gupta, Laxmidhar Behera, Venkatesh K. S.
EVOW
2010
Springer
15 years 10 months ago
Multi-Objective Probability Collectives
We describe and evaluate a multi-objective optimisation (MOO) algorithm that works within the Probability Collectives (PC) optimisation framework. PC is an alternative approach to ...
Antony Waldock, David Corne
ECAI
2006
Springer
15 years 5 months ago
Calibrating Probability Density Forecasts with Multi-Objective Search
Abstract. In this paper, we show that the optimization of density forecasting models for regression in machine learning can be formulated as a multi-objective problem. We describe ...
Michael Carney, Padraig Cunningham