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» Using Active Learning in Intrusion Detection
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IEEEARES
2008
IEEE
15 years 5 months ago
Effective Monitoring of a Survivable Distributed Networked Information System
In 2002, DARPA put together a challenging proposition to the research community: demonstrate using an existing information system and available DARPA developed and other COTS tech...
Paul Rubel, Michael Atighetchi, Partha Pratim Pal,...
TCSV
2008
297views more  TCSV 2008»
14 years 10 months ago
Activity Analysis, Summarization, and Visualization for Indoor Human Activity Monitoring
Abstract--In this work, we study how continuous video monitoring and intelligent video processing can be used in eldercare to assist the independent living of elders and to improve...
Zhongna Zhou, Xi Chen, Yu-Chia Chung, Zhihai He, T...
ICRA
2010
IEEE
137views Robotics» more  ICRA 2010»
14 years 9 months ago
Robot reinforcement learning using EEG-based reward signals
Abstract— Reinforcement learning algorithms have been successfully applied in robotics to learn how to solve tasks based on reward signals obtained during task execution. These r...
Iñaki Iturrate, Luis Montesano, Javier Ming...
KDD
2005
ACM
158views Data Mining» more  KDD 2005»
15 years 11 months ago
Adversarial learning
Many classification tasks, such as spam filtering, intrusion detection, and terrorism detection, are complicated by an adversary who wishes to avoid detection. Previous work on ad...
Daniel Lowd, Christopher Meek
ICDM
2005
IEEE
187views Data Mining» more  ICDM 2005»
15 years 4 months ago
Parallel Algorithms for Distance-Based and Density-Based Outliers
An outlier is an observation that deviates so much from other observations as to arouse suspicion that it was generated by a different mechanism. Outlier detection has many applic...
Elio Lozano, Edgar Acuña