Results 141 to 150 of about 1,405,222 (160)

Subthreshold moment analysis of neuronal populations driven by synchronous synaptic inputs. [PDF]

PLoS Comput Biol
Becker LA, Baccelli F, Taillefumier T.
europepmc   +1 more source

Network Flow-Control Using Asynchronous Stochastic Approximation

2007 46th IEEE Conference on Decision and Control, 2007
We propose several stochastic approximation implementations for related algorithms in flow-control of communication networks. First, a discrete-time implementation of Kelly's primal flow-control algorithm is proposed. Convergence with probability 1 is shown, even in the presence of communication delays and stochastic effects seen in link congestion ...
Shalabh Bhatnagar
exaly   +5 more sources

The Borkar–Meyn Theorem for Asynchronous Stochastic Approximations

Systems and Control Letters, 2011
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Shalabh Bhatnagar
exaly   +5 more sources

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Asymptotic Behavior of Asynchronous Stochastic Approximation

Science in China Series F: Information Sciences, 2001
The pathwise convergence of a distributed, asynchronous stochastic approximation (SA) scheme is analyzed. The conditions imposed on the step size and noise are the weakest in comparison with the existing ones. The step sizes in different processors are allowed to be different, and the time-delays between processors are also allowed to be different and ...
Haitao Fang, Hanfu Chen
exaly   +3 more sources

Asynchronous Distributed Principal Component Analysis Using Stochastic Approximation

2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 2012
In this paper we address the problem of asynchronous distributed principal component analysis. We provide several algorithms coping with different situations according to the underlying graph structure. A general enough framework allows us to analyze all these algorithms at the same time.
Pascal Bianchi, Jeremie Jakubowicz
exaly   +2 more sources

Asynchronous Stochastic Approximation Algorithms for Networked Systems: Regime-Switching Topologies and Multiscale Structure

Multiscale Modeling and Simulation, 2013
This work develops asynchronous stochastic approximation (SA) algorithms for networked systems with multiagents and regime-switching topologies to achieve consensus control. There are several distinct features of the algorithms: (1) In contrast to most of the existing consensus algorithms, the participating agents compute and communicate in an ...
Le Yi Wang, Gang George Yin
exaly   +2 more sources

Concentration of Contractive Stochastic Approximation and Reinforcement Learning [PDF]

Stochastic Systems, 2022
Using a martingale concentration inequality, concentration bounds `from time $n_0$ on' are derived for stochastic approximation algorithms with contractive maps and both martingale difference and Markov noises. These are applied to reinforcement learning
Vivek Borkar, Siddharth Chandak, Parth Dodhia   +2 more
exaly   +1 more source

Erratum: Asynchronous Stochastic Approximations

SIAM Journal on Control and Optimization, 2000
The proofs of Lemma 2.1 and Theorem 3.2 of [1] have a common error, the correction of which needs additional conditions: the use of l’Hopital’s rule in both equates the limiting ratio of derivatives of functions with the limiting ratio of the functions themselves, but this presupposes that the latter exist.
openaire   +1 more source

The O.D.E. Method for Convergence of Stochastic Approximation and Reinforcement Learning

SIAM Journal on Control and Optimization, 2000
It is shown here that stability of the stochastic approximation algorithm is implied by the asymptotic stability of the origin for an associated ODE. This in turn implies convergence of the algorithm. Several specific classes of algorithms are considered
S P Meyn, V S Borkar
exaly   +2 more sources