Distributed discrete resource optimization in heterogeneous networks

COVID-19 lethality reduction using artificial intelligence solutions derived from telecommunications systems

“…With all data elements being known, the problem can be relatively easily solved with the resolution method developed in Ref. [ 29 ]. This method is based on solving the dual problem with convex optimization techniques.…”

Distributed Derivative-free Optimization in Large Communication Networks with Sparse Activity

“…Our derivative-free optimization problem is known as zero-order stochastic optimization and bandit optimization. There are numbers of work based on two-point gradient estimator, e.g., [12], [13], [14], [15], under the assumption that two values of the objective function f (a (1) k ; s k ) and f (a (2) k ; s k ) are available under the same stochastic parameter s k . However such assumption is unrealistic in our setting, e.g., in i.i.d.…”

“…k ; s k ) and f (a (2) k ; s k ) are available under the same stochastic parameter s k . However such assumption is unrealistic in our setting, e.g., in i.i.d.…”

“…The local utility of any active node is a function of the action of all the active nodes, as well as some stochastic environment state that can be seen as a non-additive stochastic process, e.g., stochastic and time-varying channel gain in wireless communication system. Such stochastic optimization problem is important for the improvement of network performance and has attracted much attention in various field, e.g., radio resource management [2], power control [3], [4], and beamforming allocation [5].…”