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» A Theory for Memory-Based Learning
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111
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ECIS
2003
15 years 6 months ago
Implications of constructivism for computer-based learning
Constructivism has gained popularity recently, but it is not a completely new learning paradigm. Much of the work within Information Systems Science (IS) and especially within ele...
Timo Lainema
SOFSEM
1999
Springer
15 years 9 months ago
Coherent Concepts, Robust Learning
We study learning scenarios in which multiple learners are involved and “nature” imposes some constraints that force the predictions of these learners to behave coherently. Thi...
Dan Roth, Dmitry Zelenko
CCS
2006
ACM
15 years 8 months ago
Can machine learning be secure?
Machine learning systems offer unparalled flexibility in dealing with evolving input in a variety of applications, such as intrusion detection systems and spam e-mail filtering. H...
Marco Barreno, Blaine Nelson, Russell Sears, Antho...
ATAL
2009
Springer
15 years 11 months ago
Multiagent reinforcement learning: algorithm converging to Nash equilibrium in general-sum discounted stochastic games
This paper introduces a multiagent reinforcement learning algorithm that converges with a given accuracy to stationary Nash equilibria in general-sum discounted stochastic games. ...
Natalia Akchurina
157
Voted
CVPR
1997
IEEE
15 years 9 months ago
Learning Generic Prior Models for Visual Computation
This paper presents a novel theory for learning generic prior models from a set of observed natural images based on a minimax entropy theory that the authors studied in modeling t...
Song Chun Zhu, David Mumford