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JMLR
2010
132views more  JMLR 2010»
15 years 1 months ago
Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence
The problems of dimension reduction and inference of statistical dependence are addressed by the modeling framework of learning gradients. The models we propose hold for Euclidean...
Qiang Wu, Justin Guinney, Mauro Maggioni, Sayan Mu...
GANDC
2011
93views more  GANDC 2011»
14 years 6 months ago
Bayesian spatial modeling and interpolation using copulas
Copulas have attracted much attention in spatial statistics over the past few years. They are used as a flexible alternative to traditional methods for nonGaussian spatial modelin...
Hannes Kazianka, Jürgen Pilz
JSS
2008
89views more  JSS 2008»
15 years 6 months ago
A search-based framework for automatic testing of MATLAB/Simulink models
Search-based test-data generation has proved successful for code-level testing but almost no search-based work has been carried out at evels of abstraction. In this paper the appl...
Yuan Zhan, John A. Clark
ICIP
2005
IEEE
16 years 6 days ago
Robust highlight extraction using multi-stream hidden Markov models for baseball video
This paper proposes a robust statistical framework to extract highlights from a baseball broadcast video. We applied multistream Hidden Markov Models (HMMs) to control the weights...
Nguyen Huu Bach, Koichi Shinoda, Sadaoki Furui
SIGCOMM
2000
ACM
15 years 11 months ago
A stochastic model of TCP/IP with stationary random
In this paper, we present a model for TCP/IP ow control mechanism. The rate at which data is transmitted increases linearly in time until a packet loss is detected. At that point,...
Eitan Altman, Konstantin Avrachenkov, Chadi Baraka...