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» Learning from Highly Structured Data by Decomposition
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OOPSLA
1998
Springer
15 years 2 months ago
Visualizing Dynamic Software System Information Through High-Level Models
Dynamic information collected as a software system executes can help software engineers perform some tasks on a system more effectively. To interpret the sizable amount of data ge...
Robert J. Walker, Gail C. Murphy, Bjørn N. ...
LISA
2007
15 years 15 days ago
NetADHICT: A Tool for Understanding Network Traffic
Computer and network administrators are often confused or uncertain about the behavior of their networks. Traditional analysis using IP ports, addresses, and protocols are insuffi...
Hajime Inoue, Dana Jansens, Abdulrahman Hijazi, An...
99
Voted
CIDM
2009
IEEE
15 years 5 months ago
A new hybrid method for Bayesian network learning With dependency constraints
Abstract— A Bayes net has qualitative and quantitative aspects: The qualitative aspect is its graphical structure that corresponds to correlations among the variables in the Baye...
Oliver Schulte, Gustavo Frigo, Russell Greiner, We...
GROUP
2005
ACM
15 years 3 months ago
Proactive behaviour may lead to failure in virtual project-based collaborative learning
This paper argues that proactive behaviour, caused by high engagement and motivation of the learners, may lead to failure of collaborative learning. By examining empirical data fr...
Pernille Bjørn, Morten Hertzum
114
Voted
ICIP
2007
IEEE
15 years 12 months ago
Monocular Tracking 3D People By Gaussian Process Spatio-Temporal Variable Model
Tracking 3D people from monocular video is often poorly constrained. To mitigate this problem, prior knowledge should be exploited. In this paper, the Gaussian process spatio-temp...
Junbiao Pang, Laiyun Qing, Qingming Huang, Shuqian...