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» Termination Analysis with Algorithmic Learning
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110
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GECCO
2008
Springer
261views Optimization» more  GECCO 2008»
15 years 1 months ago
SSNNS -: a suite of tools to explore spiking neural networks
We are interested in engineering smart machines that enable backtracking of emergent behaviors. Our SSNNS simulator consists of hand-picked tools to explore spiking neural network...
Heike Sichtig, J. David Schaffer, Craig B. Laramee
115
Voted
BMCBI
2010
182views more  BMCBI 2010»
15 years 19 days ago
L2-norm multiple kernel learning and its application to biomedical data fusion
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
Shi Yu, Tillmann Falck, Anneleen Daemen, Lé...
ML
2008
ACM
15 years 14 days ago
Incremental exemplar learning schemes for classification on embedded devices
Although memory-based classifiers offer robust classification performance, their widespread usage on embedded devices is hindered due to the device's limited memory resources...
Ankur Jain, Daniel Nikovski
107
Voted
CORR
2010
Springer
109views Education» more  CORR 2010»
15 years 19 days ago
Polynomial Learning of Distribution Families
Abstract--The question of polynomial learnability of probability distributions, particularly Gaussian mixture distributions, has recently received significant attention in theoreti...
Mikhail Belkin, Kaushik Sinha
NECO
2007
150views more  NECO 2007»
15 years 23 hour ago
Reinforcement Learning, Spike-Time-Dependent Plasticity, and the BCM Rule
Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is ...
Dorit Baras, Ron Meir