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» Results Merging Algorithm Using Multiple Regression Models
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KDD
2004
ACM
117views Data Mining» more  KDD 2004»
16 years 2 months ago
Regularized multi--task learning
Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
Theodoros Evgeniou, Massimiliano Pontil
ICCV
2011
IEEE
14 years 2 months ago
Kinecting the dots: Particle Based Scene Flow from depth sensors
The motion field of a scene can be used for object segmentation and to provide features for classification tasks like action recognition. Scene flow is the full 3D motion fiel...
Simon Hadfield, Richard Bowden
WSC
2004
15 years 3 months ago
A Framework for Adaptive Synchronization of Distributed Simulations
Increased complexity of simulation models and the related modeling needs for global supply chains have necessitated the execution of simulations on multiple processors. While dist...
Bertan Altuntas, Richard A. Wysk
CVPR
2006
IEEE
15 years 8 months ago
Measure Locally, Reason Globally: Occlusion-sensitive Articulated Pose Estimation
Part-based tree-structured models have been widely used for 2D articulated human pose-estimation. These approaches admit efficient inference algorithms while capturing the import...
Leonid Sigal, Michael J. Black
DIS
2008
Springer
15 years 3 months ago
Empirical Asymmetric Selective Transfer in Multi-objective Decision Trees
We consider learning tasks where multiple target variables need to be predicted. Two approaches have been used in this setting: (a) build a separate single-target model for each ta...
Beau Piccart, Jan Struyf, Hendrik Blockeel