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» Statistical Modelling of CSP Solving Algorithms Performance
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CORR
2010
Springer
228views Education» more  CORR 2010»
13 years 7 months ago
Sparse Inverse Covariance Selection via Alternating Linearization Methods
Gaussian graphical models are of great interest in statistical learning. Because the conditional independencies between different nodes correspond to zero entries in the inverse c...
Katya Scheinberg, Shiqian Ma, Donald Goldfarb
TPDS
2008
117views more  TPDS 2008»
13 years 8 months ago
Energy-Efficient Thermal-Aware Task Scheduling for Homogeneous High-Performance Computing Data Centers: A Cyber-Physical Approac
High Performance Computing data centers have been rapidly growing, both in number and size. Thermal management of data centers can address dominant problems associated with cooling...
Qinghui Tang, Sandeep K. S. Gupta, Georgios Varsam...
KDD
2010
ACM
274views Data Mining» more  KDD 2010»
14 years 25 days ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
WSDM
2012
ACM
245views Data Mining» more  WSDM 2012»
12 years 4 months ago
The early bird gets the buzz: detecting anomalies and emerging trends in information networks
In this work we propose a novel approach to anomaly detection in streaming communication data. We first build a stochastic model for the system based on temporal communication pa...
Brian Thompson
ESWA
2007
146views more  ESWA 2007»
13 years 9 months ago
A real-valued genetic algorithm to optimize the parameters of support vector machine for predicting bankruptcy
Two parameters, C and r, must be carefully predetermined in establishing an efficient support vector machine (SVM) model. Therefore, the purpose of this study is to develop a gene...
Chih-Hung Wu, Gwo-Hshiung Tzeng, Yeong-Jia Goo, We...