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» Causal inference using the algorithmic Markov condition
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ICML
2009
IEEE
15 years 10 months ago
Exploiting sparse Markov and covariance structure in multiresolution models
We consider Gaussian multiresolution (MR) models in which coarser, hidden variables serve to capture statistical dependencies among the finest scale variables. Tree-structured MR ...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
ICML
2010
IEEE
14 years 10 months ago
Conditional Topic Random Fields
Generative topic models such as LDA are limited by their inability to utilize nontrivial input features to enhance their performance, and many topic models assume that topic assig...
Jun Zhu, Eric P. Xing
ICASSP
2011
IEEE
14 years 1 months ago
On the success of network inference using a markov routing model
In this paper we discuss why a simple network topology inference algorithm based on network co-occurrence measurements and a Markov random walk model for routing enables perfect t...
Laura Balzano, Robert Nowak, Matthew Roughan
WSDM
2010
ACM
322views Data Mining» more  WSDM 2010»
15 years 7 months ago
Inferring Search Behaviors Using Partially Observable Markov (POM) Model
This article describes an application of the partially observable Markov (POM) model to the analysis of a large scale commercial web search log. Mathematically, POM is a variant o...
Kuansan Wang, Nikolas Gloy, Xiaolong Li
IRAL
2003
ACM
15 years 3 months ago
Question-Answering based on virtually integrated lexical knowledge base
This paper proposes an algorithm for causality inference based on a set of lexical knowledge bases that contain information about such items as event role, is-a hierarchy, relevan...
Key-Sun Choi, Jae-Ho Kim, Masaru Miyazaki, Jun Got...