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ICDIM
2007
IEEE
15 years 8 months ago
Predicting durability in DHTs using Markov chains
We consider the problem of data durability in lowbandwidth large-scale distributed storage systems. Given the limited bandwidth between replicas, these systems suffer from long re...
Fabio Picconi, Bruno Baynat, Pierre Sens
CORR
2006
Springer
76views Education» more  CORR 2006»
15 years 6 months ago
Inconsistent parameter estimation in Markov random fields: Benefits in the computation-limited setting
Consider the problem of joint parameter estimation and prediction in a Markov random field: i.e., the model parameters are estimated on the basis of an initial set of data, and th...
Martin J. Wainwright
APIN
2004
107views more  APIN 2004»
15 years 6 months ago
Designing Polymer Blends Using Neural Networks, Genetic Algorithms, and Markov Chains
In this paper we present a new technique to simulate polymer blends that overcomes the shortcomings in polymer system modeling. This method has an inherent advantage in that the v...
N. K. Roy, Walter D. Potter, D. P. Landau
CORR
2010
Springer
163views Education» more  CORR 2010»
15 years 4 months ago
Faster Rates for training Max-Margin Markov Networks
Structured output prediction is an important machine learning problem both in theory and practice, and the max-margin Markov network (M3 N) is an effective approach. All state-of-...
Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan
ICIP
2010
IEEE
15 years 4 months ago
3D augmented Markov random field for object recognition
In this paper, we propose to use 3D information to augment the Markov random field (MRF) model for object recognition. Conventional MRF for image-based object recognition usually ...
Wei Yu, Ahmed Bilal Ashraf, Yao-Jen Chang, Congcon...