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» A Hierarchical Latent Variable Model for Data Visualization
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KDD
2004
ACM
210views Data Mining» more  KDD 2004»
14 years 9 months ago
Web usage mining based on probabilistic latent semantic analysis
The primary goal of Web usage mining is the discovery of patterns in the navigational behavior of Web users. Standard approaches, such as clustering of user sessions and discoveri...
Xin Jin, Yanzan Zhou, Bamshad Mobasher
IJON
2011
133views more  IJON 2011»
13 years 3 months ago
Relational generative topographic mapping
Abstract. The generative topographic mapping (GTM) has been proposed as a statistical model to represent high dimensional data by means of a sparse lattice of points in latent spac...
Andrej Gisbrecht, Bassam Mokbel, Barbara Hammer
ICML
2006
IEEE
14 years 9 months ago
The rate adapting poisson model for information retrieval and object recognition
Probabilistic modelling of text data in the bagof-words representation has been dominated by directed graphical models such as pLSI, LDA, NMF, and discrete PCA. Recently, state of...
Peter V. Gehler, Alex Holub, Max Welling
ECCV
2008
Springer
14 years 10 months ago
Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks
Abstract. Building visual recognition models that adapt across different domains is a challenging task for computer vision. While feature-learning machines in the form of hierarchi...
Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric P. Xi...
NIPS
1998
13 years 10 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