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IJCNN
2006
IEEE
16 years 29 days 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
WSC
1997
15 years 8 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
PRL
2008
97views more  PRL 2008»
15 years 6 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
ILP
2007
Springer
16 years 1 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 7 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....