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» Anomaly Detection Using Visualization and Machine Learning
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KDD
2004
ACM
330views Data Mining» more  KDD 2004»
15 years 10 months ago
Learning to detect malicious executables in the wild
In this paper, we describe the development of a fielded application for detecting malicious executables in the wild. We gathered 1971 benign and 1651 malicious executables and enc...
Jeremy Z. Kolter, Marcus A. Maloof
ICML
2005
IEEE
15 years 10 months ago
Q-learning of sequential attention for visual object recognition from informative local descriptors
This work provides a framework for learning sequential attention in real-world visual object recognition, using an architecture of three processing stages. The first stage rejects...
Lucas Paletta, Gerald Fritz, Christin Seifert
ICML
2010
IEEE
14 years 11 months ago
Deep networks for robust visual recognition
Deep Belief Networks (DBNs) are hierarchical generative models which have been used successfully to model high dimensional visual data. However, they are not robust to common vari...
Yichuan Tang, Chris Eliasmith
MM
2006
ACM
152views Multimedia» more  MM 2006»
15 years 3 months ago
Multimodal fusion using learned text concepts for image categorization
Conventional image categorization techniques primarily rely on low-level visual cues. In this paper, we describe a multimodal fusion scheme which improves the image classification...
Qiang Zhu, Mei-Chen Yeh, Kwang-Ting Cheng
KDD
2004
ACM
210views Data Mining» more  KDD 2004»
15 years 10 months ago
Visually mining and monitoring massive time series
Moments before the launch of every space vehicle, engineering discipline specialists must make a critical go/no-go decision. The cost of a false positive, allowing a launch in spi...
Jessica Lin, Eamonn J. Keogh, Stefano Lonardi, Jef...