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» Learning Generative Models via Discriminative Approaches
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ICML
2010
IEEE
13 years 10 months ago
Asymptotic Analysis of Generative Semi-Supervised Learning
Semi-supervised learning has emerged as a popular framework for improving modeling accuracy while controlling labeling cost. Based on an extension of stochastic composite likeliho...
Joshua Dillon, Krishnakumar Balasubramanian, Guy L...
ICCV
2009
IEEE
13 years 6 months ago
Real-time visual tracking via Incremental Covariance Tensor Learning
Visual tracking is a challenging problem, as an object may change its appearance due to pose variations, illumination changes, and occlusions. Many algorithms have been proposed t...
Yi Wu, Jian Cheng, Jinqiao Wang, Hanqing Lu
SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
11 years 11 months ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...
AIED
2005
Springer
14 years 2 months ago
Generating Reports of Graphical Modelling Processes for Authoring and Presentation
Today's computer supported modelling environments could provide much more information about the users’ actions and problem solving processes than they usually store for late...
Lars Bollen
IJCNN
2008
IEEE
14 years 3 months ago
Learning adaptive subject-independent P300 models for EEG-based brain-computer interfaces
Abstract— This paper proposes an approach to learn subjectindependent P300 models for EEG-based brain-computer interfaces. The P300 models are first learned using a pool of exis...
Shijian Lu, Cuntai Guan, Haihong Zhang