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103
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NCI
2004
185views Neural Networks» more  NCI 2004»
15 years 1 months ago
Hierarchical reinforcement learning with subpolicies specializing for learned subgoals
This paper describes a method for hierarchical reinforcement learning in which high-level policies automatically discover subgoals, and low-level policies learn to specialize for ...
Bram Bakker, Jürgen Schmidhuber
ECAL
2007
Springer
15 years 5 months ago
Neural Uncertainty and Sensorimotor Robustness
Real organisms live in a world full of uncertain situations and have evolved cognitive mechanisms to cope with problems based on actions and perceptions which are not always reliab...
Jose A. Fernandez-Leon, Ezequiel A. Di Paolo
ECAL
2003
Springer
15 years 4 months ago
Pattern Recognition in a Bucket
This paper demonstrates that the waves produced on the surface of water can be used as the medium for a “Liquid State Machine” that pre-processes inputs so allowing a simple pe...
Chrisantha Fernando, Sampsa Sojakka
118
Voted
JCNS
2000
165views more  JCNS 2000»
14 years 11 months ago
A Population Density Approach That Facilitates Large-Scale Modeling of Neural Networks: Analysis and an Application to Orientati
We explore a computationally efficient method of simulating realistic networks of neurons introduced by Knight, Manin, and Sirovich (1996) in which integrate-and-fire neurons are ...
Duane Q. Nykamp, Daniel Tranchina
146
Voted
ECCV
2004
Springer
16 years 1 months ago
A Biologically Motivated and Computationally Tractable Model of Low and Mid-Level Vision Tasks
This paper presents a biologically motivated model for low and mid-level vision tasks and its interpretation in computer vision terms. Initially we briefly present the biologically...
Iasonas Kokkinos, Rachid Deriche, Petros Maragos, ...