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ICML
1999
IEEE
14 years 8 months ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox
WWW
2005
ACM
14 years 8 months ago
A uniform approach to accelerated PageRank computation
In this note we consider a simple reformulation of the traditional power iteration algorithm for computing the stationary distribution of a Markov chain. Rather than communicate t...
Frank McSherry
KDD
2009
ACM
182views Data Mining» more  KDD 2009»
14 years 8 months ago
Scalable graph clustering using stochastic flows: applications to community discovery
Algorithms based on simulating stochastic flows are a simple and natural solution for the problem of clustering graphs, but their widespread use has been hampered by their lack of...
Venu Satuluri, Srinivasan Parthasarathy
KDD
2005
ACM
117views Data Mining» more  KDD 2005»
14 years 8 months ago
Rule extraction from linear support vector machines
We describe an algorithm for converting linear support vector machines and any other arbitrary hyperplane-based linear classifiers into a set of non-overlapping rules that, unlike...
Glenn Fung, Sathyakama Sandilya, R. Bharat Rao
STOC
2006
ACM
180views Algorithms» more  STOC 2006»
14 years 8 months ago
Pricing for fairness: distributed resource allocation for multiple objectives
In this paper, we present a simple distributed algorithm for resource allocation which simultaneously approximates the optimum value for a large class of objective functions. In p...
Sung-woo Cho, Ashish Goel