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ICASSP
2011
IEEE
14 years 5 months ago
Joint dictionary learning and topic modeling for image clustering
A new Bayesian model is proposed, integrating dictionary learning and topic modeling into a unified framework. The model is applied to cluster multiple images, and a subset of th...
Lingbo Li, Mingyuan Zhou, Eric Wang, Lawrence Cari...
KDD
2006
ACM
240views Data Mining» more  KDD 2006»
16 years 1 months ago
Adaptive event detection with time-varying poisson processes
Time-series of count data are generated in many different contexts, such as web access logging, freeway traffic monitoring, and security logs associated with buildings. Since this...
Alexander T. Ihler, Jon Hutchins, Padhraic Smyth
ICML
2010
IEEE
15 years 2 months ago
Gaussian Process Change Point Models
We combine Bayesian online change point detection with Gaussian processes to create a nonparametric time series model which can handle change points. The model can be used to loca...
Yunus Saatci, Ryan Turner, Carl Edward Rasmussen
ICDM
2009
IEEE
155views Data Mining» more  ICDM 2009»
15 years 8 months ago
Stacked Gaussian Process Learning
—Triggered by a market relevant application that involves making joint predictions of pedestrian and public transit flows in urban areas, we address the question of how to utili...
Marion Neumann, Kristian Kersting, Zhao Xu, Daniel...
NIPS
2003
15 years 2 months ago
Hierarchical Topic Models and the Nested Chinese Restaurant Process
We address the problem of learning topic hierarchies from data. The model selection problem in this domain is daunting—which of the large collection of possible trees to use? We...
David M. Blei, Thomas L. Griffiths, Michael I. Jor...