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KDD
2009
ACM
180views Data Mining» more  KDD 2009»
14 years 6 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy
ICMCS
2007
IEEE
194views Multimedia» more  ICMCS 2007»
13 years 12 months ago
Automatically Tuning Background Subtraction Parameters using Particle Swarm Optimization
A common trait of background subtraction algorithms is that they have learning rates, thresholds, and initial values that are hand-tuned for a scenario in order to produce the des...
Brandyn White, Mubarak Shah
JAIR
1998
198views more  JAIR 1998»
13 years 5 months ago
Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Alberto Ruiz, Pedro E. López-de-Teruel, M. ...
ICIP
2006
IEEE
14 years 7 months ago
Sparse Image Reconstruction using Sparse Priors
Sparse image reconstruction is of interest in the fields of radioastronomy and molecular imaging. The observation is assumed to be a linear transformation of the image, and corrup...
Michael Ting, Raviv Raich, Alfred O. Hero
CSE
2009
IEEE
14 years 11 days ago
Predicting Interests of People on Online Social Networks
—We introduce a new data set which contains both a self-declared friendship network and self-chosen attributes from a finite list defined by the social networking site. We prop...
Apoorv Agarwal, Owen Rambow, Nandini Bhardwaj