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» Learning Approximate Consistencies
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UAI
2004
15 years 3 months ago
Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
Iain Murray, Zoubin Ghahramani
123
Voted
ICDM
2007
IEEE
124views Data Mining» more  ICDM 2007»
15 years 8 months ago
Community Learning by Graph Approximation
Learning communities from a graph is an important problem in many domains. Different types of communities can be generalized as link-pattern based communities. In this paper, we p...
Bo Long, Xiaoyun Xu, Zhongfei (Mark) Zhang, Philip...
EACL
2006
ACL Anthology
15 years 3 months ago
Online Learning of Approximate Dependency Parsing Algorithms
In this paper we extend the maximum spanning tree (MST) dependency parsing framework of McDonald et al. (2005c) to incorporate higher-order feature representations and allow depen...
Ryan T. McDonald, Fernando C. N. Pereira
177
Voted
JMLR
2010
186views more  JMLR 2010»
14 years 8 months ago
Dimensionality Estimation, Manifold Learning and Function Approximation using Tensor Voting
We address instance-based learning from a perceptual organization standpoint and present methods for dimensionality estimation, manifold learning and function approximation. Under...
Philippos Mordohai, Gérard G. Medioni
114
Voted
VIS
2009
IEEE
212views Visualization» more  VIS 2009»
16 years 3 months ago
Applying Manifold Learning to Plotting Approximate Contour Trees
Shigeo Takahashi, Issei Fujishiro, Masato Okada