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ICML
2008
IEEE
16 years 7 months ago
Training restricted Boltzmann machines using approximations to the likelihood gradient
A new algorithm for training Restricted Boltzmann Machines is introduced. The algorithm, named Persistent Contrastive Divergence, is different from the standard Contrastive Diverg...
Tijmen Tieleman
ACL
2006
15 years 8 months ago
Unsupervised Relation Disambiguation Using Spectral Clustering
This paper presents an unsupervised learning approach to disambiguate various relations between name entities by use of various lexical and syntactic features from the contexts. I...
Jinxiu Chen, Dong-Hong Ji, Chew Lim Tan, Zheng-Yu ...
SODA
2001
ACM
147views Algorithms» more  SODA 2001»
15 years 8 months ago
Sublinear time approximate clustering
Clustering is of central importance in a number of disciplines including Machine Learning, Statistics, and Data Mining. This paper has two foci: 1 It describes how existing algori...
Nina Mishra, Daniel Oblinger, Leonard Pitt
CVPR
2008
IEEE
16 years 9 months ago
Recognition by association via learning per-exemplar distances
We pose the recognition problem as data association. In this setting, a novel object is explained solely in terms of a small set of exemplar objects to which it is visually simila...
Tomasz Malisiewicz, Alexei A. Efros
ILP
2004
Springer
16 years 7 days ago
Learning Ensembles of First-Order Clauses for Recall-Precision Curves: A Case Study in Biomedical Information Extraction
Many domains in the field of Inductive Logic Programming (ILP) involve highly unbalanced data. Our research has focused on Information Extraction (IE), a task that typically invol...
Mark Goadrich, Louis Oliphant, Jude W. Shavlik