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TJS
2010
182views more  TJS 2010»
15 years 4 months ago
A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning
This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
Yasser Yasami, Saadat Pour Mozaffari
ISSTA
2010
ACM
15 years 10 months ago
Learning from 6, 000 projects: lightweight cross-project anomaly detection
Real production code contains lots of knowledge—on the domain, on the architecture, and on the environment. How can we leverage this knowledge in new projects? Using a novel lig...
Natalie Gruska, Andrzej Wasylkowski, Andreas Zelle...
ACL
2012
13 years 8 months ago
Fast Online Training with Frequency-Adaptive Learning Rates for Chinese Word Segmentation and New Word Detection
We present a joint model for Chinese word segmentation and new word detection. We present high dimensional new features, including word-based features and enriched edge (label-tra...
Xu Sun, Houfeng Wang, Wenjie Li
NIPS
2004
15 years 7 months ago
Active Learning for Anomaly and Rare-Category Detection
We introduce a novel active-learning scenario in which a user wants to work with a learning algorithm to identify useful anomalies. These are distinguished from the traditional st...
Dan Pelleg, Andrew W. Moore
TIP
2008
86views more  TIP 2008»
15 years 6 months ago
Learning the Dynamics and Time-Recursive Boundary Detection of Deformable Objects
We propose a principled framework for recursively segmenting deformable objects across a sequence of frames. We demonstrate the usefulness of this method on left ventricular segmen...
Walter Sun, Müjdat Çetin, Raymond C. C...