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CVPR
2008
IEEE
16 years 8 months ago
Incremental learning of nonparametric Bayesian mixture models
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...
Ryan Gomes, Max Welling, Pietro Perona
CHI
2009
ACM
16 years 7 months ago
Learning how: the search for craft knowledge on the internet
Communicating the subtleties of a craft technique, like putting a zipper into a garment or throwing a clay pot, can be challenging even when working side by side. Yet HowTo conten...
Cristen Torrey, Elizabeth F. Churchill, David W. M...
ICIAP
2009
ACM
16 years 1 months ago
Towards a Theoretical Framework for Learning Multi-modal Patterns for Embodied Agents
Multi-modality is a fundamental feature that characterizes biological systems and lets them achieve high robustness in understanding skills while coping with uncertainty. Relativel...
Nicoletta Noceti, Barbara Caputo, Claudio Castelli...
ICRA
2009
IEEE
121views Robotics» more  ICRA 2009»
16 years 1 months ago
Learning sequential visual attention control through dynamic state space discretization
² Similar to humans and primates, artificial creatures like robots are limited in terms of allocation of their resources to huge sensory and perceptual information. Serial process...
Ali Borji, Majid Nili Ahmadabadi, Babak Nadjar Ara...
GECCO
2009
Springer
194views Optimization» more  GECCO 2009»
16 years 1 months ago
Combining evolution strategy and gradient descent method for discriminative learning of bayesian classifiers
The optimization method is one of key issues in discriminative learning of pattern classifiers. This paper proposes a hybrid approach of the Covariance Matrix Adaptation Evolution...
Xuefeng Chen, Xiabi Liu, Yunde Jia