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» Information Theory, Inference, and Learning Algorithms
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NIPS
2008
13 years 9 months ago
Analyzing human feature learning as nonparametric Bayesian inference
Almost all successful machine learning algorithms and cognitive models require powerful representations capturing the features that are relevant to a particular problem. We draw o...
Joseph Austerweil, Thomas L. Griffiths
ICML
2003
IEEE
14 years 8 months ago
Finding Underlying Connections: A Fast Graph-Based Method for Link Analysis and Collaboration Queries
Many techniques in the social sciences and graph theory deal with the problem of examining and analyzing patterns found in the underlying structure and associations of a group of ...
Jeremy Kubica, Andrew W. Moore, David Cohn, Jeff G...
JMLR
2010
163views more  JMLR 2010»
13 years 2 months ago
Dense Message Passing for Sparse Principal Component Analysis
We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
Kevin Sharp, Magnus Rattray
BMCBI
2010
135views more  BMCBI 2010»
13 years 8 months ago
GIGA: a simple, efficient algorithm for gene tree inference in the genomic age
Background: Phylogenetic relationships between genes are not only of theoretical interest: they enable us to learn about human genes through the experimental work on their relativ...
Paul D. Thomas
MM
2005
ACM
134views Multimedia» more  MM 2005»
14 years 1 months ago
Graph based multi-modality learning
To better understand the content of multimedia, a lot of research efforts have been made on how to learn from multi-modal feature. In this paper, it is studied from a graph point ...
Hanghang Tong, Jingrui He, Mingjing Li, Changshui ...