Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Shah, Suhail M"'
We consider network-based decentralized optimization problems, where each node in the network possesses a local function and the objective is to collectively attain a consensus solution that minimizes the sum of all the local functions. A major chall
Externí odkaz:
http://arxiv.org/abs/2309.02626
Autor:
Shah, Suhail M., Bollapragada, Raghu
Decentralized optimization is typically studied under the assumption of noise-free transmission. However, real-world scenarios often involve the presence of noise due to factors such as additive white Gaussian noise channels or probabilistic quantiza
Externí odkaz:
http://arxiv.org/abs/2307.14942
Autor:
Shah, Suhail M.
We study the regret of simulated annealing (SA) based approaches to solving discrete stochastic optimization problems. The main theoretical conclusion is that the regret of the simulated annealing algorithm, with either noisy or noiseless observation
Externí odkaz:
http://arxiv.org/abs/2009.06188
We introduce a model of graph-constrained dynamic choice with reinforcement modeled by positively $\alpha$-homogeneous rewards. We show that its empirical process, which can be written as a stochastic approximation recursion with Markov noise, has th
Externí odkaz:
http://arxiv.org/abs/2007.03983
We consider the consensual distributed optimization problem and propose an asynchronous version of the Alternating Direction Method of Multipliers (ADMM) algorithm to solve it. The `asynchronous' part here refers to the fact that only one node/proces
Externí odkaz:
http://arxiv.org/abs/1810.05067
Autor:
Shah, Suhail M
We propose several variants of the Frank-Wolfe algorithm to minimize a sum of functions. The main proposed algorithm is inspired from the dual averaging scheme of Nesterov adapted for Frank Wolfe in a stochastic setting. A distributed version of this
Externí odkaz:
http://arxiv.org/abs/1805.10200
Autor:
Shah, Suhail M.
The standard theory of stochastic approximation (SA) is extended to the case when the constraint set is a Riemannian manifold. Specifically, the standard ODE method for analyzing SA schemes is extended to iterations constrained to stay on a manifold
Externí odkaz:
http://arxiv.org/abs/1711.10754
Autor:
Shah, Suhail M.
We consider the consensual distributed optimization problem in the Riemannian context. Specifically, the minimization of a sum of functions form is studied where each individual function in the sum is located at the node of a network. An algorithm, w
Externí odkaz:
http://arxiv.org/abs/1711.11196
Autor:
Shah, Suhail M., Borkar, Vivek S.
We propose a distributed version of a stochastic approximation scheme constrained to remain in the intersection of a finite family of convex sets. The projection to the intersection of these sets is also computed in a distributed manner and a `nonlin
Externí odkaz:
http://arxiv.org/abs/1708.08246
Autor:
Shah, Suhail M., Borkar, Vivek S.
Publikováno v:
In Systems & Control Letters March 2018 113:45-51
