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CVPR
2010
IEEE
14 years 5 months ago
What's going on? Discovering Spatio-Temporal Dependencies in Dynamic Scenes
We present two novel methods to automatically learn spatio-temporal dependencies of moving agents in complex dynamic scenes. They allow to discover temporal rules, such as the rig...
Daniel Kuettel, Michael Breitenstein, Luc Van Gool...
KDD
2004
ACM
132views Data Mining» more  KDD 2004»
14 years 9 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
TASLP
2008
154views more  TASLP 2008»
13 years 9 months ago
Capturing Local Variability for Speaker Normalization in Speech Recognition
The new model reduces the impact of local spectral and temporal variability by estimating a finite set of spectral and temporal warping factors which are applied to speech at the f...
Antonio Miguel, Eduardo Lleida, Richard Rose, Luis...
DKE
2007
130views more  DKE 2007»
13 years 9 months ago
Enabling access-privacy for random walk based data analysis applications
Random walk graph and Markov chain based models are used heavily in many data and system analysis domains, including web, bioinformatics, and queuing. These models enable the desc...
Ping Lin, K. Selçuk Candan
GLVLSI
2005
IEEE
118views VLSI» more  GLVLSI 2005»
14 years 2 months ago
A continuous time markov decision process based on-chip buffer allocation methodology
We have presented an optimal on-chip buffer allocation and buffer insertion methodology which uses stochastic models of the architecture. This methodology uses finite buffer s...
Sankalp Kallakuri, Nattawut Thepayasuwan, Alex Dob...