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ISCAS
2006
IEEE
144views Hardware» more  ISCAS 2006»
15 years 8 months ago
A VLSI spike-driven dynamic synapse which learns only when necessary
— We describe an analog VLSI circuit implementing spike-driven synaptic plasticity, embedded in a network of integrate-and-fire neurons. This biologically inspired synapse is hi...
S. Mitra, Stefano Fusi, Giacomo Indiveri
ITNG
2010
IEEE
15 years 7 months ago
A Forecasting Capability Study of Empirical Mode Decomposition for the Arrival Time of a Parallel Batch System
This paper demonstrates the feasibility and potential of applying empirical mode decomposition (EMD) to forecast the arrival time behaviors in a parallel batch system. An analysis...
Linh Ngo, Amy W. Apon, Doug Hoffman
ECAL
2001
Springer
15 years 6 months ago
Evolution of Reinforcement Learning in Uncertain Environments: Emergence of Risk-Aversion and Matching
Reinforcement learning (RL) is a fundamental process by which organisms learn to achieve a goal from interactions with the environment. Using Artificial Life techniques we derive ...
Yael Niv, Daphna Joel, Isaac Meilijson, Eytan Rupp...
109
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NIPS
1994
15 years 3 months ago
A Connectionist Technique for Accelerated Textual Input: Letting a Network Do the Typing
Each yearpeoplespendahugeamountoftimetyping. Thetextpeopletype typically contains a tremendousamount of redundancy due to predictable word usage patterns and the text's struc...
Dean Pomerleau
NECO
2007
258views more  NECO 2007»
15 years 1 months ago
Reinforcement Learning Through Modulation of Spike-Timing-Dependent Synaptic Plasticity
The persistent modification of synaptic efficacy as a function of the relative timing of pre- and postsynaptic spikes is a phenomenon known as spiketiming-dependent plasticity (...
Razvan V. Florian