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UAI
2001
15 years 7 months ago
Learning the Dimensionality of Hidden Variables
A serious problem in learning probabilistic models is the presence of hidden variables. These variables are not observed, yet interact with several of the observed variables. Dete...
Gal Elidan, Nir Friedman
ICPR
2010
IEEE
15 years 4 months ago
Semi-supervised Graph Learning: Near Strangers or Distant Relatives
In this paper, an easily implemented semi-supervised graph learning method is presented for dimensionality reduction and clustering, using the most of prior knowledge from limited...
Weifu Chen, Guocan Feng
COLT
2004
Springer
15 years 11 months ago
Regularization and Semi-supervised Learning on Large Graphs
We consider the problem of labeling a partially labeled graph. This setting may arise in a number of situations from survey sampling to information retrieval to pattern recognition...
Mikhail Belkin, Irina Matveeva, Partha Niyogi
EDM
2010
150views Data Mining» more  EDM 2010»
15 years 7 months ago
Modeling Learning Trajectories with Epistemic Network Analysis: A Simulation-based Investigation of a Novel Analytic Method for
Epistemic games are designed to help players develop domain-specific expertise that characterizes how professionals in a particular domain reason, communicate, and act [1, 11]. To ...
Andre A. Rupp, Shauna J. Sweet, Younyoung Choi
AAAI
2006
15 years 7 months ago
Multi-Conditional Learning: Generative/Discriminative Training for Clustering and Classification
This paper presents multi-conditional learning (MCL), a training criterion based on a product of multiple conditional likelihoods. When combining the traditional conditional proba...
Andrew McCallum, Chris Pal, Gregory Druck, Xuerui ...