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» Tackling Large State Spaces in Performance Modelling
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WWW
2009
ACM
14 years 9 months ago
Matchbox: large scale online bayesian recommendations
We present a probabilistic model for generating personalised recommendations of items to users of a web service. The Matchbox system makes use of content information in the form o...
David H. Stern, Ralf Herbrich, Thore Graepel
ICML
2005
IEEE
14 years 9 months ago
Core Vector Regression for very large regression problems
In this paper, we extend the recently proposed Core Vector Machine algorithm to the regression setting by generalizing the underlying minimum enclosing ball problem. The resultant...
Ivor W. Tsang, James T. Kwok, Kimo T. Lai
EDBT
2010
ACM
185views Database» more  EDBT 2010»
13 years 11 months ago
Probabilistic threshold k nearest neighbor queries over moving objects in symbolic indoor space
The availability of indoor positioning renders it possible to deploy location-based services in indoor spaces. Many such services will benefit from the efficient support for k n...
Bin Yang 0002, Hua Lu, Christian S. Jensen
UAI
2008
13 years 10 months ago
Projected Subgradient Methods for Learning Sparse Gaussians
Gaussian Markov random fields (GMRFs) are useful in a broad range of applications. In this paper we tackle the problem of learning a sparse GMRF in a high-dimensional space. Our a...
John Duchi, Stephen Gould, Daphne Koller
SPIN
2000
Springer
14 years 15 days ago
Model Checking Based on Simultaneous Reachability Analysis
Abstract. Simultaneous reachability analysis SRA is a recently proposed approach to alleviating the state space explosion problem in reachability analysis of concurrent systems. Th...
Bengi Karaçali, Kuo-Chung Tai