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» On regularization algorithms in learning theory
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NIPS
2004
15 years 6 months ago
New Criteria and a New Algorithm for Learning in Multi-Agent Systems
We propose a new set of criteria for learning algorithms in multi-agent systems, one that is more stringent and (we argue) better justified than previous proposed criteria. Our cr...
Rob Powers, Yoav Shoham
ISCAS
2008
IEEE
169views Hardware» more  ISCAS 2008»
15 years 11 months ago
Sigma-delta learning for super-resolution independent component analysis
— Many source separation algorithms fail to deliver robust performance in presence of artifacts introduced by cross-channel redundancy, non-homogeneous mixing and highdimensional...
Amin Fazel, Shantanu Chakrabartty
JMLR
2010
132views more  JMLR 2010»
14 years 11 months ago
On the Impact of Kernel Approximation on Learning Accuracy
Kernel approximation is commonly used to scale kernel-based algorithms to applications containing as many as several million instances. This paper analyzes the effect of such appr...
Corinna Cortes, Mehryar Mohri, Ameet Talwalkar
ALDT
2009
Springer
207views Algorithms» more  ALDT 2009»
15 years 11 months ago
Anytime Self-play Learning to Satisfy Functional Optimality Criteria
We present an anytime multiagent learning approach to satisfy any given optimality criterion in repeated game self-play. Our approach is opposed to classical learning approaches fo...
Andriy Burkov, Brahim Chaib-draa
JALC
2007
90views more  JALC 2007»
15 years 4 months ago
Learning Unary Automata
We determine the complexity of learning problems for unary regular languages. We begin by investigating the minimum consistent dfa (resp. nfa) problem which is known not to be app...
Gregor Gramlich, Ralf Herrmann