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» Incremental Dependency Parsing Using Online Learning
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ML
1998
ACM
102views Machine Learning» more  ML 1998»
13 years 7 months ago
Statistical Mechanics of Online Learning of Drifting Concepts: A Variational Approach
We review the application of statistical mechanics methods to the study of online learning of a drifting concept in the limit of large systems. The model where a feed-forward netwo...
Renato Vicente, Osame Kinouchi, Nestor Caticha
HUMO
2007
Springer
14 years 1 months ago
Boosted Multiple Deformable Trees for Parsing Human Poses
Tree-structured models have been widely used for human pose estimation, in either 2D or 3D. While such models allow efficient learning and inference, they fail to capture additiona...
Yang Wang 0003, Greg Mori
AAAI
2011
12 years 7 months ago
An Online Spectral Learning Algorithm for Partially Observable Nonlinear Dynamical Systems
Recently, a number of researchers have proposed spectral algorithms for learning models of dynamical systems—for example, Hidden Markov Models (HMMs), Partially Observable Marko...
Byron Boots, Geoffrey J. Gordon
CIKM
2006
Springer
13 years 11 months ago
Incremental hierarchical clustering of text documents
Incremental hierarchical text document clustering algorithms are important in organizing documents generated from streaming on-line sources, such as, Newswire and Blogs. However, ...
Nachiketa Sahoo, Jamie Callan, Ramayya Krishnan, G...
SIGIR
2008
ACM
13 years 7 months ago
Query dependent ranking using K-nearest neighbor
Many ranking models have been proposed in information retrieval, and recently machine learning techniques have also been applied to ranking model construction. Most of the existin...
Xiubo Geng, Tie-Yan Liu, Tao Qin, Andrew Arnold, H...