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APIN
1999
107views more  APIN 1999»
13 years 7 months ago
Massively Parallel Probabilistic Reasoning with Boltzmann Machines
We present a method for mapping a given Bayesian network to a Boltzmann machine architecture, in the sense that the the updating process of the resulting Boltzmann machine model pr...
Petri Myllymäki
PKDD
2010
Springer
148views Data Mining» more  PKDD 2010»
13 years 6 months ago
Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models
Abstract. A new method is proposed for compiling causal independencies into Markov logic networks (MLNs). An MLN can be viewed as compactly representing a factorization of a joint ...
Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasa...
CORR
2011
Springer
168views Education» more  CORR 2011»
12 years 11 months ago
Link Prediction by De-anonymization: How We Won the Kaggle Social Network Challenge
— This paper describes the winning entry to the IJCNN 2011 Social Network Challenge run by Kaggle.com. The goal of the contest was to promote research on realworld link predictio...
Arvind Narayanan, Elaine Shi, Benjamin I. P. Rubin...
SSPR
2004
Springer
14 years 26 days ago
Optimizing Classification Ensembles via a Genetic Algorithm for a Web-Based Educational System
Classification fusion combines multiple classifications of data into a single classification solution of greater accuracy. Feature extraction aims to reduce the computational cost ...
Behrouz Minaei-Bidgoli, Gerd Kortemeyer, William F...
SIGIR
2011
ACM
12 years 10 months ago
A boosting approach to improving pseudo-relevance feedback
Pseudo-relevance feedback has proven effective for improving the average retrieval performance. Unfortunately, many experiments have shown that although pseudo-relevance feedback...
Yuanhua Lv, ChengXiang Zhai, Wan Chen