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» Using Machine Learning to Focus Iterative Optimization
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IROS
2009
IEEE
206views Robotics» more  IROS 2009»
15 years 9 months ago
Bayesian reinforcement learning in continuous POMDPs with gaussian processes
— Partially Observable Markov Decision Processes (POMDPs) provide a rich mathematical model to handle realworld sequential decision processes but require a known model to be solv...
Patrick Dallaire, Camille Besse, Stéphane R...
HT
2009
ACM
15 years 9 months ago
Improving recommender systems with adaptive conversational strategies
Conversational recommender systems (CRSs) assist online users in their information-seeking and decision making tasks by supporting an interactive process. Although these processes...
Tariq Mahmood, Francesco Ricci
CVPR
2010
IEEE
15 years 11 months ago
Safety in Numbers: Learning Categories from Few Examples with Multi Model Knowledge Transfer
Learning object categories from small samples is a challenging problem, where machine learning tools can in general provide very few guarantees. Exploiting prior knowledge may be ...
Tatiana Tommasi, Francesco Orabona, Barbara Caputo
BIBE
2009
IEEE
131views Bioinformatics» more  BIBE 2009»
15 years 6 months ago
Learning Scaling Coefficient in Possibilistic Latent Variable Algorithm from Complex Diagnosis Data
—The Possibilistic Latent Variable (PLV) clustering algorithm is a powerful tool for the analysis of complex datasets due to its robustness toward data distributions of different...
Zong-Xian Yin
SCIA
2009
Springer
161views Image Analysis» more  SCIA 2009»
15 years 9 months ago
A Fast Optimization Method for Level Set Segmentation
Abstract. Level set methods are a popular way to solve the image segmentation problem in computer image analysis. A contour is implicitly represented by the zero level of a signed ...
Thord Andersson, Gunnar Läthén, Reiner...