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» Two Algorithms for Inducing Causal Models from Data
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CORR
2010
Springer
236views Education» more  CORR 2010»
13 years 3 months ago
Precise, Scalable and Online Request Tracing for Multi-tier Services of Black Boxes
As more and more multi-tier services are developed from commercial off-the-shelf components or heterogeneous middleware without source code available, both developers and administr...
Bo Sang, Jianfeng Zhan, Zhihong Zhang, Lei Wang, D...
ISCA
1998
IEEE
135views Hardware» more  ISCA 1998»
14 years 1 days ago
Branch Prediction Based on Universal Data Compression Algorithms
Data compression and prediction are closely related. Thus prediction methods based on data compression algorithms have been suggested for the branch prediction problem. In this wo...
Eitan Federovsky, Meir Feder, Shlomo Weiss
ACCV
1998
Springer
14 years 21 days ago
Comparison of Mean Field Annealing and Multiresolution Analysis in Missing Data Estimation
The project we are working on is to help develop and test a low cost, large area, high resolution X-ray detection system with a high dynamic range. The large area is achieved by b...
Hairong Qi, Wesley E. Snyder, Griff L. Bilbro
ICCV
2011
IEEE
12 years 8 months ago
Perturb-and-MAP Random Fields: Using Discrete Optimization\\to Learn and Sample from Energy Models
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
George Papandreou, Alan L. Yuille
DSS
2007
127views more  DSS 2007»
13 years 8 months ago
Large-scale regulatory network analysis from microarray data: modified Bayesian network learning and association rule mining
We present two algorithms for learning large-scale gene regulatory networks from microarray data: a modified informationtheory-based Bayesian network algorithm and a modified asso...
Zan Huang, Jiexun Li, Hua Su, George S. Watts, Hsi...