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SYNASC
2005
IEEE
97views Algorithms» more  SYNASC 2005»
15 years 3 months ago
A Reinforcement Learning Algorithm for Spiking Neural Networks
The paper presents a new reinforcement learning mechanism for spiking neural networks. The algorithm is derived for networks of stochastic integrate-and-fire neurons, but it can ...
Razvan V. Florian
IJCAI
1993
14 years 11 months ago
Learning Finite Automata Using Local Distinguishing Experiments
One of the open problems listed in Rivest and Schapire, 1989] is whether and how that the copies of L in their algorithm can be combined into one for better performance. This pape...
Wei-Mein Shen
HICSS
2005
IEEE
159views Biometrics» more  HICSS 2005»
15 years 3 months ago
A Repeatable Collaboration Process for Usability Testing
Evaluating the usability of an application is a crucial activity in systems development projects. It is often done collaboratively, involving groups of current or future users, us...
Gert-Jan de Vreede, Ann L. Fruhling, Anita Chakrap...
NIPS
2007
14 years 11 months ago
Theoretical Analysis of Learning with Reward-Modulated Spike-Timing-Dependent Plasticity
Reward-modulated spike-timing-dependent plasticity (STDP) has recently emerged as a candidate for a learning rule that could explain how local learning rules at single synapses su...
Robert A. Legenstein, Dejan Pecevski, Wolfgang Maa...
DAGSTUHL
2004
14 years 11 months ago
Learning with Local Models
Next to prediction accuracy, the interpretability of models is one of the fundamental criteria for machine learning algorithms. While high accuracy learners have intensively been e...
Stefan Rüping