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SIAMIS
2011
15 years 1 months ago
Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models
Abstract. Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or superresolution, can be addressed by maxi...
Matthias W. Seeger, Hannes Nickisch
IUI
2005
ACM
15 years 12 months ago
Building intelligent shopping assistants using individual consumer models
This paper describes an Intelligent Shopping Assistant designed for a shopping cart mounted tablet PC that enables individual interactions with customers. We use machine learning ...
Chad M. Cumby, Andrew E. Fano, Rayid Ghani, Marko ...
168
Voted
HICSS
2003
IEEE
220views Biometrics» more  HICSS 2003»
15 years 11 months ago
Applications of Hidden Markov Models to Detecting Multi-Stage Network Attacks
This paper describes a novel approach using Hidden Markov Models (HMM) to detect complex Internet attacks. These attacks consist of several steps that may occur over an extended pe...
Dirk Ourston, Sara Matzner, William Stump, Bryan H...
AIME
2009
Springer
15 years 11 months ago
Prediction of Mechanical Lung Parameters Using Gaussian Process Models
Abstract. Mechanical ventilation can cause severe lung damage by inadequate adjustment of the ventilator. We introduce a Machine Learning approach to predict the pressure-dependent...
Steven Ganzert, Stefan Kramer, Knut Möller, D...
JCB
2008
159views more  JCB 2008»
15 years 6 months ago
BayesMD: Flexible Biological Modeling for Motif Discovery
We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fa...
Man-Hung Eric Tang, Anders Krogh, Ole Winther