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NIPS
2007
13 years 8 months ago
Learning to classify complex patterns using a VLSI network of spiking neurons
We propose a compact, low power VLSI network of spiking neurons which can learn to classify complex patterns of mean firing rates on–line and in real–time. The network of int...
Srinjoy Mitra, Giacomo Indiveri, Stefano Fusi
ICML
2009
IEEE
14 years 2 months ago
Active learning for directed exploration of complex systems
Physics-based simulation codes are widely used in science and engineering to model complex systems that would be infeasible to study otherwise. Such codes provide the highest-fid...
Michael C. Burl, Esther Wang
EWLR
1997
Springer
13 years 11 months ago
Learning Complex Robot Behaviours by Evolutionary Computing with Task Decomposition
Building robots can be a tough job because the designer has to predict the interactions between the robot and the environment as well as to deal with them. One solution to cope the...
Wei-Po Lee, John Hallam, Henrik Hautop Lund
AAAI
2007
13 years 9 months ago
A Reinforcement Learning Algorithm with Polynomial Interaction Complexity for Only-Costly-Observable MDPs
An Unobservable MDP (UMDP) is a POMDP in which there are no observations. An Only-Costly-Observable MDP (OCOMDP) is a POMDP which extends an UMDP by allowing a particular costly a...
Roy Fox, Moshe Tennenholtz
IUI
2009
ACM
14 years 4 months ago
Learning to generalize for complex selection tasks
Selection tasks are common in modern computer interfaces: we are often required to select a set of files, emails, data entries, and the like. File and data browsers have sorting a...
Alan Ritter, Sumit Basu