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NIPS
1998
13 years 8 months ago
Learning from Dyadic Data
Dyadic data refers to a domain with two nite sets of objects in which observations are made for dyads, i.e., pairs with one element from either set. This type of data arises natur...
Thomas Hofmann, Jan Puzicha, Michael I. Jordan
IDA
2009
Springer
13 years 4 months ago
Hierarchical Extraction of Independent Subspaces of Unknown Dimensions
Abstract. Independent Subspace Analysis (ISA) is an extension of Independent Component Analysis (ICA) that aims to linearly transform a random vector such as to render groups of it...
Peter Gruber, Harold W. Gutch, Fabian J. Theis
FCSC
2010
238views more  FCSC 2010»
13 years 4 months ago
Knowledge discovery through directed probabilistic topic models: a survey
Graphical models have become the basic framework for topic based probabilistic modeling. Especially models with latent variables have proved to be effective in capturing hidden str...
Ali Daud, Juanzi Li, Lizhu Zhou, Faqir Muhammad
HT
2003
ACM
13 years 12 months ago
Link analysis for collaborative knowledge building
We present an ongoing research project utilizing navigation and hyperlink data to aid collaborative knowledge building. We allow collaborators to personally organize documents and...
Harris Wu, Michael D. Gordon, Kurt DeMaagd, Nathan...
JIIS
2002
114views more  JIIS 2002»
13 years 6 months ago
A Dynamic Probabilistic Model to Visualise Topic Evolution in Text Streams
Abstract. We propose a novel probabilistic method, based on latent variable models, for unsupervised topographic visualisation of dynamically evolving, coherent textual information...
Ata Kabán, Mark Girolami