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» Preference learning with Gaussian processes
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122
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ICASSP
2011
IEEE
14 years 6 months ago
Rapid speaker adaptation with speaker adaptive training and non-negative matrix factorization
In this paper, we describe a novel speaker adaptation algorithm based on Gaussian mixture weight adaptation. A small number of latent speaker vectors are estimated with non-negati...
Xueru Zhang, Kris Demuynck, Hugo Van hamme
ICASSP
2011
IEEE
14 years 6 months ago
Collaborative system for signal processing education
In this paper we present a collaborative system designed to develop problem solving skills in learners through problemcentric exercises. This system is part of a data collection s...
Gregory A. Krudysz, James H. McClellan
146
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ICIAR
2010
Springer
14 years 12 months ago
Image Segmentation for Robots: Fast Self-adapting Gaussian Mixture Model
Image segmentation is a critical low-level visual routine for robot perception. However, most image segmentation approaches are still too slow to allow real-time robot operation. I...
Nicola Greggio, Alexandre Bernardino, José ...
130
Voted
IROS
2009
IEEE
155views Robotics» more  IROS 2009»
15 years 9 months ago
Active learning using mean shift optimization for robot grasping
— When children learn to grasp a new object, they often know several possible grasping points from observing a parent’s demonstration and subsequently learn better grasps by tr...
Oliver Kroemer, Renaud Detry, Justus H. Piater, Ja...
133
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CIKM
2011
Springer
14 years 2 months ago
A probabilistic method for inferring preferences from clicks
Evaluating rankers using implicit feedback, such as clicks on documents in a result list, is an increasingly popular alternative to traditional evaluation methods based on explici...
Katja Hofmann, Shimon Whiteson, Maarten de Rijke