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ISNN
2011
Springer
12 years 10 months ago
Orthogonal Feature Learning for Time Series Clustering
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Xiaozhe Wang, Leo Lopes
ICPR
2010
IEEE
13 years 6 months ago
Data-Driven Lung Nodule Models for Robust Nodule Detection in Chest CT
The quality of the lung nodule models determines the success of lung nodule detection. This paper describes aspects of our data-driven approach for modeling lung nodules using the...
Amal Farag, James Graham, Aly A. Farag
ATAL
2003
Springer
14 years 19 days ago
Minimizing communication cost in a distributed Bayesian network using a decentralized MDP
In complex distributed applications, a problem is often decomposed into a set of subproblems that are distributed to multiple agents. We formulate this class of problems with a tw...
Jiaying Shen, Victor R. Lesser, Norman Carver
ICIC
2007
Springer
14 years 1 months ago
Evolutionary Ensemble for In Silico Prediction of Ames Test Mutagenicity
Driven by new regulations and animal welfare, the need to develop in silico models has increased recently as alternative approaches to safety assessment of chemicals without animal...
Huanhuan Chen, Xin Yao
WWW
2007
ACM
14 years 8 months ago
Identifying and discriminating between web and peer-to-peer traffic in the network core
Traffic classification is the ability to identify and categorize network traffic by application type. In this paper, we consider the problem of traffic classification in the netwo...
Jeffrey Erman, Anirban Mahanti, Martin F. Arlitt, ...