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» Preference learning with Gaussian processes
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130
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ICASSP
2011
IEEE
14 years 7 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
112
Voted
ICASSP
2011
IEEE
14 years 7 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
152
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ICIAR
2010
Springer
15 years 25 days 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 ...
IROS
2009
IEEE
155views Robotics» more  IROS 2009»
15 years 10 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...
141
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CIKM
2011
Springer
14 years 3 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