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AI
2011
Springer
15 years 1 months ago
Learning qualitative models from numerical data
Qualitative models are often a useful abstraction of the physical world. Learning qualitative models from numerical data sible way to obtain such an abstraction. We present a new ...
Jure Zabkar, Martin Mozina, Ivan Bratko, Janez Dem...
AROBOTS
2011
15 years 1 months ago
Learning GP-BayesFilters via Gaussian process latent variable models
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...
Jonathan Ko, Dieter Fox
ADMA
2010
Springer
271views Data Mining» more  ADMA 2010»
15 years 1 months ago
Exploiting Concept Clumping for Efficient Incremental E-Mail Categorization
We introduce a novel approach to incremental e-mail categorization based on identifying and exploiting "clumps" of messages that are classified similarly. Clumping reflec...
Alfred Krzywicki, Wayne Wobcke
CDC
2010
IEEE
146views Control Systems» more  CDC 2010»
15 years 1 months ago
Adaptive autonomous soaring of multiple UAVs using Simultaneous Perturbation Stochastic Approximation
Abstract-- This paper presents a new algorithm for maximizing the flight duration of a single UAV (Uninhabited Air Vehicle) and UAVs group using the thermal model developed by Alle...
Cathrine Antal, Oleg Granichin, Sergey Levi
CDC
2010
IEEE
169views Control Systems» more  CDC 2010»
15 years 1 months ago
Consensus-based distributed linear filtering
We address the consensus-based distributed linear filtering problem, where a discrete time, linear stochastic process is observed by a network of sensors. We assume that the consen...
Ion Matei, John S. Baras
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