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» A Framework for Multiple-Instance Learning
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ICRA
2008
IEEE
185views Robotics» more  ICRA 2008»
16 years 1 months ago
Humanoid teleoperation for whole body manipulation
— We present results of successful telemanipulation of large, heavy objects by a humanoid robot. Using a single joystick the operator controls walking and whole body manipulation...
Mike Stilman, Koichi Nishiwaki, Satoshi Kagami
162
Voted
CEC
2007
IEEE
16 years 1 months ago
Bayesian inference in estimation of distribution algorithms
— Metaheuristics such as Estimation of Distribution Algorithms and the Cross-Entropy method use probabilistic modelling and inference to generate candidate solutions in optimizat...
Marcus Gallagher, Ian Wood, Jonathan M. Keith, Geo...
159
Voted
ICDM
2007
IEEE
106views Data Mining» more  ICDM 2007»
16 years 1 months ago
High-Speed Function Approximation
We address a new learning problem where the goal is to build a predictive model that minimizes prediction time (the time taken to make a prediction) subject to a constraint on mod...
Biswanath Panda, Mirek Riedewald, Johannes Gehrke,...
157
Voted
ICRA
2007
IEEE
165views Robotics» more  ICRA 2007»
16 years 1 months ago
Probabilistic Appearance Based Navigation and Loop Closing
— This paper describes a probabilistic framework for navigation using only appearance data. By learning a generative model of appearance, we can compute not only the similarity o...
Mark Cummins, Paul M. Newman
222
Voted
ISBI
2007
IEEE
16 years 1 months ago
Shape Analysis Using Curvature-Based Descriptors and Profile Hidden Markov Models
This paper presents a new framework for shape modeling and analysis. A shape instance is described by a curvature-based shape descriptor. A Profile Hidden Markov Model (PHMM) is ...
Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas