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» A distributed machine learning framework
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114
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ICCV
2009
IEEE
16 years 5 months ago
Level Set Segmentation with Both Shape and Intensity Priors
We present a new variational level-set-based segmentation formulation that uses both shape and intensity prior information learned from a training set. By applying Bayes’ rule...
Siqi Chen and Richard J. Radke
124
Voted
WSDM
2012
ACM
301views Data Mining» more  WSDM 2012»
13 years 8 months ago
Learning evolving and emerging topics in social media: a dynamic nmf approach with temporal regularization
As massive repositories of real-time human commentary, social media platforms have arguably evolved far beyond passive facilitation of online social interactions. Rapid analysis o...
Ankan Saha, Vikas Sindhwani
95
Voted
SDM
2008
SIAM
105views Data Mining» more  SDM 2008»
15 years 2 months ago
Gaussian Process Learning for Cyber-Attack Early Warning
Network security has been a serious concern for many years. For example, firewalls often record thousands of exploit attempts on a daily basis. Network administrators could benefi...
Jian Zhang 0004, Phillip A. Porras, Johannes Ullri...
98
Voted
ECML
2003
Springer
15 years 6 months ago
Optimizing Local Probability Models for Statistical Parsing
Abstract. This paper studies the properties and performance of models for estimating local probability distributions which are used as components of larger probabilistic systems ...
Kristina Toutanova, Mark Mitchell, Christopher D. ...
105
Voted
PPSN
2010
Springer
14 years 11 months ago
Indirect Encoding of Neural Networks for Scalable Go
Abstract. The game of Go has attracted much attention from the artificial intelligence community. A key feature of Go is that humans begin to learn on a small board, and then incr...
Jason Gauci, Kenneth O. Stanley