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ITCC
2005
IEEE
16 years 5 days ago
A Scalable Generative Topographic Mapping for Sparse Data Sequences
We propose a novel, computationally efficient generative topographic model for inferring low dimensional representations of high dimensional data sets, designed to exploit data s...
Ata Kabán
AAAI
2006
15 years 8 months ago
A Fast Decision Tree Learning Algorithm
There is growing interest in scaling up the widely-used decision-tree learning algorithms to very large data sets. Although numerous diverse techniques have been proposed, a fast ...
Jiang Su, Harry Zhang
ICPR
2010
IEEE
15 years 4 months ago
Cross Entropy Optimization of the Random Set Framework for Multiple Instance Learning
Abstract--Multiple instance learning (MIL) is a recently researched technique used for learning a target concept in the presence of noise. Previously, a random set framework for mu...
Jeremy Bolton, Paul D. Gader
ICIP
2009
IEEE
16 years 7 months ago
Learning Large Margin Likelihoods For Realtime Head Pose Tracking
We consider the problem of head tracking and pose estimation in realtime from low resolution images. Tracking and pose recognition are treated as two coupled problems in a probabi...
ICML
2003
IEEE
16 years 7 months ago
Learning Mixture Models with the Latent Maximum Entropy Principle
We present a new approach to estimating mixture models based on a new inference principle we have proposed: the latent maximum entropy principle (LME). LME is different both from ...
Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin...