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ESANN
2000
13 years 11 months ago
Discriminative learning for neural decision feedback equalizers
In this work new Decision-Feedback (DF) Neural Equalizers (DFNE) are introduced and compared with classical DF equalizers and Viterbi demodulators. It is shown that the choice of ...
Elio D. Di Claudio, Raffaele Parisi, Gianni Orland...
NIPS
1992
13 years 11 months ago
A Note on Learning Vector Quantization
Vector Quantization is useful for data compression. Competitive Learning which minimizes reconstruction error is an appropriate algorithm for vector quantization of unlabelled dat...
Virginia R. de Sa, Dana H. Ballard
CORR
2010
Springer
146views Education» more  CORR 2010»
13 years 10 months ago
Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization
Solving stochastic optimization problems under partial observability, where one needs to adaptively make decisions with uncertain outcomes, is a fundamental but notoriously diffic...
Daniel Golovin, Andreas Krause
KI
2008
Springer
13 years 10 months ago
Learning by Observing: Case-Based Decision Making in Complex Strategy Games
Abstract. There is a growing research interest in the design of competitive and adaptive Game AI for complex computer strategy games. In this paper, we present a novel approach for...
Darko Obradovic, Armin Stahl
JMLR
2010
119views more  JMLR 2010»
13 years 4 months ago
Semi-Supervised Learning via Generalized Maximum Entropy
Various supervised inference methods can be analyzed as convex duals of the generalized maximum entropy (MaxEnt) framework. Generalized MaxEnt aims to find a distribution that max...
Ayse Erkan, Yasemin Altun