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16 years 8 months ago
Gaussian Processes for Machine Learning
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
MMM
2006
Springer
128views Multimedia» more  MMM 2006»
15 years 3 months ago
An improved distortion model for rate control of DCT-based video coding
This paper presents a rate control algorithm for the dominant discrete cosine transform (DCT) -based video coding. It is developed based on a more accurate rate-distortion (RD) mo...
Jun Xie, Liang-Tien Chia, Bu-Sung Lee
LREC
2010
148views Education» more  LREC 2010»
14 years 11 months ago
POS Multi-tagging Based on Combined Models
In the POS tagging task, there are two kinds of statistical models: one is generative model, such as the HMM, the others are discriminative models, such as the Maximum Entropy Mod...
Yan Zhao, Gertjan van Noord
BPM
2008
Springer
188views Business» more  BPM 2008»
14 years 12 months ago
Social Software for Modeling Business Processes
Abstract. The aim of this paper is to show how the use of social networks may help users to behave as modelers they trust. Users are guided in this respect within the context of an...
Agnes Koschmider, Minseok Song, Hajo A. Reijers
FORTE
2008
14 years 11 months ago
An SMT Approach to Bounded Reachability Analysis of Model Programs
Model programs represent transition systems that are used fy expected behavior of systems at a high level of abstraction. The main application area is application-level network pro...
Margus Veanes, Nikolaj Bjørner, Alexander R...