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» Selectivity Estimation using Probabilistic Models
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IMC
2004
ACM
15 years 8 months ago
Modeling distances in large-scale networks by matrix factorization
In this paper, we propose a model for representing and predicting distances in large-scale networks by matrix factorization. The model is useful for network distance sensitive app...
Yun Mao, Lawrence K. Saul
168
Voted
ICTAI
2010
IEEE
14 years 12 months ago
Unsupervised Greedy Learning of Finite Mixture Models
This work deals with a new technique for the estimation of the parameters and number of components in a finite mixture model. The learning procedure is performed by means of a expe...
Nicola Greggio, Alexandre Bernardino, Cecilia Lasc...
148
Voted
CVPR
2010
IEEE
15 years 11 months ago
Chaotic Invariants of Lagrangian Particle Trajectories for Anomaly Detection in Crowded Scenes
A novel method for crowd flow modeling and anomaly detection is proposed for both coherent and incoherent scenes. The novelty is revealed in three aspects. First, it is a unique ut...
Shandong Wu, Brian E. Moore, and Mubarak Shah
93
Voted
TIP
2008
139views more  TIP 2008»
15 years 2 months ago
Model-Based 2.5-D Deconvolution for Extended Depth of Field in Brightfield Microscopy
Abstract--Due to the limited depth of field of brightfield microscopes, it is usually impossible to image thick specimens entirely in focus. By optically sectioning the specimen, t...
François Aguet, Dimitri Van De Ville, Micha...
126
Voted
JMLR
2010
157views more  JMLR 2010»
14 years 9 months ago
Combining Experiments to Discover Linear Cyclic Models with Latent Variables
We present an algorithm to infer causal relations between a set of measured variables on the basis of experiments on these variables. The algorithm assumes that the causal relatio...
Frederick Eberhardt, Patrik O. Hoyer, Richard Sche...