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116
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IJCNN
2006
IEEE
15 years 8 months ago
Backpropagation for Population-Temporal Coded Spiking Neural Networks
Abstract— Supervised learning rules for spiking neural networks are currently only able to use time-to-first-spike coding and are plagued by very irregular learning curves due t...
Benjamin Schrauwen, Jan M. Van Campenhout
114
Voted
WSC
1997
15 years 3 months ago
Activate This Classroom at Time Now
Active and cooperative learning methods represent a paradigm shift in the delivery of engineering education. These techniques recognize that the passive model of the typical colle...
Manuel D. Rossetti
108
Voted
PRL
2008
97views more  PRL 2008»
15 years 2 months ago
Repairing self-confident active-transductive learners using systematic exploration
We consider an active learning game within a transductive learning model. A major problem with many active learning algorithms is that an unreliable current hypothesis can mislead...
Ron Begleiter, Ran El-Yaniv, Dmitry Pechyony
130
Voted
ILP
2007
Springer
15 years 8 months ago
Learning Relational Options for Inductive Transfer in Relational Reinforcement Learning
In reinforcement learning problems, an agent has the task of learning a good or optimal strategy from interaction with his environment. At the start of the learning task, the agent...
Tom Croonenborghs, Kurt Driessens, Maurice Bruynoo...
ICML
2000
IEEE
16 years 3 months ago
Meta-Learning by Landmarking Various Learning Algorithms
Landmarking is a novel approach to describing tasks in meta-learning. Previous approaches to meta-learning mostly considered only statistics-inspired measures of the data as a sou...
Bernhard Pfahringer, Hilan Bensusan, Christophe G....