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APCCM
2006
13 years 9 months ago
Network data mining: methods and techniques for discovering deep linkage between attributes
Network Data Mining identifies emergent networks between myriads of individual data items and utilises special algorithms that aid visualisation of `emergent' patterns and tre...
John Galloway, Simeon J. Simoff
PLDI
2010
ACM
14 years 1 months ago
Decoupled lifeguards: enabling path optimizations for dynamic correctness checking tools
Dynamic correctness checking tools (a.k.a. lifeguards) can detect a wide array of correctness issues, such as memory, security, and concurrency misbehavior, in unmodified executa...
Olatunji Ruwase, Shimin Chen, Phillip B. Gibbons, ...
ICDCS
2010
IEEE
14 years 10 days ago
Sentomist: Unveiling Transient Sensor Network Bugs via Symptom Mining
—Wireless Sensor Network (WSN) applications are typically event-driven. While the source codes of these applications may look simple, they are executed with a complicated concurr...
Yangfan Zhou, Xinyu Chen, Michael R. Lyu, Jiangchu...
IADIS
2003
13 years 9 months ago
Query-Based Discovering of Popular Changes in WWW
This paper presents the method for retrieving and summarizing changes in topics from online resources. Users often want to know what are the major changes in their areas of intere...
Adam Jatowt, Khoo Khyou Bun, Mitsuru Ishizuka
ECCV
2010
Springer
13 years 8 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof