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» Boosted Optimization for Network Classification
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BMCBI
2010
224views more  BMCBI 2010»
14 years 9 months ago
An adaptive optimal ensemble classifier via bagging and rank aggregation with applications to high dimensional data
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...
Susmita Datta, Vasyl Pihur, Somnath Datta
ACCV
2006
Springer
14 years 11 months ago
Learning Multi-category Classification in Bayesian Framework
Abstract. We propose an algorithm for Sparse Bayesian Classification for multi-class problems using Automatic Relevance Determination(ARD). Unlike other approaches which treat mult...
Atul Kanaujia, Dimitris N. Metaxas
AI
2002
Springer
14 years 9 months ago
Ensembling neural networks: Many could be better than all
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
Zhi-Hua Zhou, Jianxin Wu, Wei Tang
MICRO
2009
IEEE
134views Hardware» more  MICRO 2009»
15 years 4 months ago
A case for dynamic frequency tuning in on-chip networks
Performance and power are the first order design metrics for Network-on-Chips (NoCs) that have become the de-facto standard in providing scalable communication backbones for mult...
Asit K. Mishra, Reetuparna Das, Soumya Eachempati,...
TEC
2010
191views more  TEC 2010»
14 years 4 months ago
Particle Swarm Optimization Aided Orthogonal Forward Regression for Unified Data Modeling
We propose a unified data modeling approach that is equally applicable to supervised regression and classification applications, as well as to unsupervised probability density func...
Sheng Chen, Xia Hong, Chris J. Harris