no code implementations • 18 Oct 2016 • Mark Eisen, Santiago Segarra, Gabriel Egan, Alejandro Ribeiro
We first study the similarity of writing styles between Early English playwrights by comparing the profile WANs.
no code implementations • 22 May 2017 • Mark Eisen, Aryan Mokhtari, Alejandro Ribeiro
In this paper, we propose a novel adaptive sample size second-order method, which reduces the cost of computing the Hessian by solving a sequence of ERM problems corresponding to a subset of samples and lowers the cost of computing the Hessian inverse using a truncated eigenvalue decomposition.
no code implementations • 2 Feb 2017 • Aryan Mokhtari, Mark Eisen, Alejandro Ribeiro
This makes their computational cost per iteration independent of the number of objective functions $n$.
no code implementations • 23 Mar 2016 • Mark Eisen, Aryan Mokhtari, Alejandro Ribeiro
The resulting dual D-BFGS method is a fully decentralized algorithm in which nodes approximate curvature information of themselves and their neighbors through the satisfaction of a secant condition.
no code implementations • 17 Jun 2014 • Santiago Segarra, Mark Eisen, Alejandro Ribeiro
Attribution accuracy is observed to exceed the one achieved by methods that rely on word frequencies alone.
no code implementations • 21 Jul 2018 • Mark Eisen, Clark Zhang, Luiz. F. O. Chamon, Daniel D. Lee, Alejandro Ribeiro
This paper considers the design of optimal resource allocation policies in wireless communication systems which are generically modeled as a functional optimization problem with stochastic constraints.
no code implementations • 21 Jun 2019 • Zhan Gao, Mark Eisen, Alejandro Ribeiro
Radio on Free Space Optics (RoFSO), as a universal platform for heterogeneous wireless services, is able to transmit multiple radio frequency signals at high rates in free space optical networks.
no code implementations • 10 Nov 2019 • Dionysios S. Kalogerias, Mark Eisen, George J. Pappas, Alejandro Ribeiro
Upon further assuming the use of near-universal policy parameterizations, we also develop explicit bounds on the gap between optimal values of initial, infinite dimensional resource allocation problems, and dual values of their parameterized smoothed surrogates.
no code implementations • 17 Feb 2020 • Navid Naderializadeh, Mark Eisen, Alejandro Ribeiro
We consider the problem of downlink power control in wireless networks, consisting of multiple transmitter-receiver pairs communicating with each other over a single shared wireless medium.
no code implementations • 26 Jun 2020 • Zhan Gao, Mark Eisen, Alejandro Ribeiro
This paper investigates the optimal resource allocation in free space optical (FSO) fronthaul networks.
no code implementations • 27 Jul 2020 • Zhan Gao, Mark Eisen, Alejandro Ribeiro
This paper investigates the general problem of resource allocation for mitigating channel fading effects in Free Space Optical (FSO) communications.
no code implementations • 5 Nov 2020 • Zhiyang Wang, Mark Eisen, Alejandro Ribeiro
We capture the asynchrony by modeling the activation pattern as a characteristic of each node and train a policy-based resource allocation method.
no code implementations • 3 Sep 2020 • Vinicius Lima, Mark Eisen, Konstantinos Gatsis, Alejandro Ribeiro
Wireless control systems replace traditional wired communication with wireless networks to exchange information between actuators, plants and sensors in a control system.
no code implementations • 4 Sep 2019 • Mark Eisen, Alejandro Ribeiro
We consider the problem of optimally allocating resources across a set of transmitters and receivers in a wireless network.
no code implementations • 3 Jul 2021 • Zhiyang Wang, Mark Eisen, Alejandro Ribeiro
We consider the broad class of decentralized optimal resource allocation problems in wireless networks, which can be formulated as a constrained statistical learning problems with a localized information structure.
no code implementations • 10 Oct 2021 • Zhiyang Wang, Luana Ruiz, Mark Eisen, Alejandro Ribeiro
We consider the problem of resource allocation in large scale wireless networks.
no code implementations • 24 Jan 2022 • Vinicius Lima, Mark Eisen, Konstantinos Gatsis, Alejandro Ribeiro
As the number of learnable parameters in a neural network grows with the size of the input signal, deep reinforcement learning may fail to scale, limiting the immediate generalization of such scheduling and resource allocation policies to large-scale systems.
no code implementations • 8 Feb 2022 • Mark Eisen, Santosh Shukla, Dave Cavalcanti, Amit S. Baxi
We consider the problem of controlling a series of industrial systems, such as industrial robotics, in a factory environment over a shared wireless channel leveraging edge computing capabilities.
no code implementations • 28 Oct 2022 • Yiğit Berkay Uslu, Navid Naderializadeh, Mark Eisen, Alejandro Ribeiro
We propose a state-augmented parameterization for the RRM policy, where alongside the instantaneous network states, the RRM policy takes as input the set of dual variables corresponding to the constraints.
1 code implementation • 5 Jul 2022 • Navid Naderializadeh, Mark Eisen, Alejandro Ribeiro
We consider resource management problems in multi-user wireless networks, which can be cast as optimizing a network-wide utility function, subject to constraints on the long-term average performance of users across the network.
1 code implementation • 7 Mar 2022 • Navid Naderializadeh, Mark Eisen, Alejandro Ribeiro
We consider the problems of user selection and power control in wireless interference networks, comprising multiple access points (APs) communicating with a group of user equipment devices (UEs) over a shared wireless medium.