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TSP
2008
105views more  TSP 2008»
13 years 4 months ago
Semi-Supervised Linear Spectral Unmixing Using a Hierarchical Bayesian Model for Hyperspectral Imagery
This paper proposes a hierarchical Bayesian model that can be used for semi-supervised hyperspectral image unmixing. The model assumes that the pixel reflectances result from linea...
Nicolas Dobigeon, Jean-Yves Tourneret, Chein-I Cha...
IJCAI
2007
13 years 6 months ago
Graph-Based Semi-Supervised Learning as a Generative Model
This paper proposes and develops a new graph-based semi-supervised learning method. Different from previous graph-based methods that are based on discriminative models, our method...
Jingrui He, Jaime G. Carbonell, Yan Liu 0002
ACL
2007
13 years 6 months ago
Guiding Semi-Supervision with Constraint-Driven Learning
Over the last few years, two of the main research directions in machine learning of natural language processing have been the study of semi-supervised learning algorithms as a way...
Ming-Wei Chang, Lev-Arie Ratinov, Dan Roth
ICML
2010
IEEE
13 years 6 months ago
High-Performance Semi-Supervised Learning using Discriminatively Constrained Generative Models
We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation c...
Gregory Druck, Andrew McCallum
ICMLA
2007
13 years 6 months ago
Semi-Supervised Active Learning for Modeling Medical Concepts from Free Text
We apply a new active learning formulation to the problem of learning medical concepts from unstructured text. The new formulation is based on maximizing the mutual information th...
Rómer Rosales, Praveen Krishnamurthy, R. Bh...