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PAMI
1998
128views more  PAMI 1998»
15 years 6 months ago
A Hierarchical Latent Variable Model for Data Visualization
—Visualization has proven to be a powerful and widely-applicable tool for the analysis and interpretation of multivariate data. Most visualization algorithms aim to find a projec...
Christopher M. Bishop, Michael E. Tipping
ICDE
1998
IEEE
142views Database» more  ICDE 1998»
16 years 8 months ago
High Dimensional Similarity Joins: Algorithms and Performance Evaluation
Current data repositories include a variety of data types, including audio, images and time series. State of the art techniques for indexing such data and doing query processing r...
Nick Koudas, Kenneth C. Sevcik
SSPR
2004
Springer
16 years 3 days ago
Clustering Variable Length Sequences by Eigenvector Decomposition Using HMM
We present a novel clustering method using HMM parameter space and eigenvector decomposition. Unlike the existing methods, our algorithm can cluster both constant and variable leng...
Fatih Murat Porikli
ICML
2008
IEEE
16 years 7 months ago
Topologically-constrained latent variable models
In dimensionality reduction approaches, the data are typically embedded in a Euclidean latent space. However for some data sets this is inappropriate. For example, in human motion...
Raquel Urtasun, David J. Fleet, Andreas Geiger, Jo...
PKDD
2005
Springer
122views Data Mining» more  PKDD 2005»
16 years 8 days ago
A Probabilistic Clustering-Projection Model for Discrete Data
For discrete co-occurrence data like documents and words, calculating optimal projections and clustering are two different but related tasks. The goal of projection is to find a ...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...