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» Exploiting Myopic Learning
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ACSAC
2003
IEEE
15 years 5 months ago
A Failure to Learn from the Past
On the evening of 2 November 1988, someone “infected” the Internet with a worm program. That program exploited flaws in utility programs in systems based on BSD-derived versi...
Eugene H. Spafford
ICMCS
2009
IEEE
132views Multimedia» more  ICMCS 2009»
14 years 9 months ago
Video face recognition with graph-based semi-supervised learning
We consider the problem of classification of multiple observations of the same object, possibly under different transformations. We view this problem as a special case of semi-sup...
Effrosini Kokiopoulou, Pascal Frossard
SMC
2007
IEEE
102views Control Systems» more  SMC 2007»
15 years 6 months ago
An improved immune Q-learning algorithm
—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
Zhengqiao Ji, Q. M. Jonathan Wu, Maher A. Sid-Ahme...
SIGMOD
2010
ACM
213views Database» more  SIGMOD 2010»
15 years 4 months ago
On active learning of record matching packages
We consider the problem of learning a record matching package (classifier) in an active learning setting. In active learning, the learning algorithm picks the set of examples to ...
Arvind Arasu, Michaela Götz, Raghav Kaushik
NIPS
2008
15 years 1 months ago
Structure Learning in Human Sequential Decision-Making
We use graphical models and structure learning to explore how people learn policies in sequential decision making tasks. Studies of sequential decision-making in humans frequently...
Daniel Acuña, Paul R. Schrater