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PKDD
2009
Springer
138views Data Mining» more  PKDD 2009»
16 years 1 months ago
Margin and Radius Based Multiple Kernel Learning
A serious drawback of kernel methods, and Support Vector Machines (SVM) in particular, is the difficulty in choosing a suitable kernel function for a given dataset. One of the appr...
Huyen Do, Alexandros Kalousis, Adam Woznica, Melan...
ICRA
2008
IEEE
173views Robotics» more  ICRA 2008»
16 years 1 months ago
Bayesian reinforcement learning in continuous POMDPs with application to robot navigation
— We consider the problem of optimal control in continuous and partially observable environments when the parameters of the model are not known exactly. Partially Observable Mark...
Stéphane Ross, Brahim Chaib-draa, Joelle Pi...
ICDM
2007
IEEE
132views Data Mining» more  ICDM 2007»
16 years 1 months ago
Learning What Makes a Society Tick
We present a machine learning methodology (models, algorithms, and experimental data) to discovering the agent dynamics that drive the evolution of the social groups in a communit...
Hung-Ching Chen, Mark K. Goldberg, Malik Magdon-Is...
CVPR
2006
IEEE
16 years 26 days ago
Learning Joint Top-Down and Bottom-up Processes for 3D Visual Inference
We present an algorithm for jointly learning a consistent bidirectional generative-recognition model that combines top-down and bottom-up processing for monocular 3d human motion ...
Cristian Sminchisescu, Atul Kanaujia, Dimitris N. ...
ICCV
2005
IEEE
16 years 13 days ago
Learning Effective Image Metrics from Few Pairwise Examples
We present a new approach to learning image metrics. The main advantage of our method lies in a formulation that requires only a few pairwise examples. Apparently, based on the li...
Hwann-Tzong Chen, Tyng-Luh Liu, Chiou-Shann Fuh