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ECCC
2006
87views more  ECCC 2006»
14 years 10 months ago
The Learnability of Quantum States
Traditional quantum state tomography requires a number of measurements that grows exponentially with the number of qubits n. But using ideas from computational learning theory, we...
Scott Aaronson
ENGL
2008
142views more  ENGL 2008»
14 years 10 months ago
A Solid-State Neuron for Spiking Neural Network Implementation
This paper presents a compact analog neuron cell incorporating an array of charge-coupled synapses connected via a common output terminal. The novel silicon synapse is based on a t...
Yajie Chen, Steve Hall, Liam McDaid, Octavian Buiu...
IAT
2008
IEEE
15 years 4 months ago
An Agent Model for a Human's Functional State and Performance
This paper presents an agent model of the dynamics of a human’s functional state in relation to task performance and environment. It can be used in agent systems that support hu...
Tibor Bosse, Fiemke Both, Rianne van Lambalgen, Ja...
CDC
2009
IEEE
127views Control Systems» more  CDC 2009»
15 years 2 months ago
A moving horizon scheme for distributed state estimation
— This paper presents a novel distributed estimation algorithm based on the concept of moving horizon estimation. Under weak observability conditions we prove convergence of the ...
Marcello Farina, Giancarlo Ferrari-Trecate, Riccar...
AUSAI
1999
Springer
15 years 2 months ago
Q-Learning in Continuous State and Action Spaces
Abstract. Q-learning can be used to learn a control policy that maximises a scalar reward through interaction with the environment. Qlearning is commonly applied to problems with d...
Chris Gaskett, David Wettergreen, Alexander Zelins...