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» Generalization Error Bounds Using Unlabeled Data
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ICMCS
2005
IEEE
92views Multimedia» more  ICMCS 2005»
14 years 2 months ago
Semi-supervised meeting event recognition with adapted HMMs
This paper investigates the use of unlabeled data to help labeled data for audio-visual event recognition in meetings. To deal with situations in which it is difficult to collect...
Dong Zhang, Daniel Gatica-Perez, Samy Bengio
NIPS
2008
13 years 9 months ago
Learning the Semantic Correlation: An Alternative Way to Gain from Unlabeled Text
In this paper, we address the question of what kind of knowledge is generally transferable from unlabeled text. We suggest and analyze the semantic correlation of words as a gener...
Yi Zhang 0010, Jeff Schneider, Artur Dubrawski
MOC
2002
83views more  MOC 2002»
13 years 8 months ago
A posteriori error estimates for general numerical methods for Hamilton-Jacobi equations. Part I: The steady state case
A new upper bound is provided for the L-norm of the difference between the viscosity solution of a model steady state Hamilton-Jacobi equation, u, and any given approximation, v. T...
Samuel Albert, Bernardo Cockburn, Donald A. French...
ICML
2005
IEEE
14 years 9 months ago
A model for handling approximate, noisy or incomplete labeling in text classification
We introduce a Bayesian model, BayesANIL, that is capable of estimating uncertainties associated with the labeling process. Given a labeled or partially labeled training corpus of...
Ganesh Ramakrishnan, Krishna Prasad Chitrapura, Ra...
JMLR
2006
186views more  JMLR 2006»
13 years 8 months ago
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
Mikhail Belkin, Partha Niyogi, Vikas Sindhwani