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UAI
2008
15 years 8 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
ML
1998
ACM
102views Machine Learning» more  ML 1998»
15 years 6 months ago
Statistical Mechanics of Online Learning of Drifting Concepts: A Variational Approach
We review the application of statistical mechanics methods to the study of online learning of a drifting concept in the limit of large systems. The model where a feed-forward netwo...
Renato Vicente, Osame Kinouchi, Nestor Caticha

Publication
314views
17 years 5 months ago
LED: Load Early Detection: A Congestion Control Algorithm based on Router Traffic Load
Efficient bandwidth allocation and low delays remain important goals, expecially in high-speed networks. Existing end-to-end congestion control schemes (such as TCP+AQM/RED) have s...
A. Durresi, P. Kandikuppa, M. Sridharan, S. Chella...
ICPR
2002
IEEE
16 years 7 months ago
Relational Graph Labelling Using Learning Techniques and Markov Random Fields
This paper introduces an approach for handling complex labelling problems driven by local constraints. The purpose is illustrated by two applications: detection of the road networ...
Denis Rivière, Jean-Francois Mangin, Jean-M...
WWW
2008
ACM
16 years 7 months ago
Offline matching approximation algorithms in exchange markets
Motivated by several marketplace applications on rapidly growing online social networks, we study the problem of efficient offline matching algorithms for online exchange markets....
Zeinab Abbassi, Laks V. S. Lakshmanan
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