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View article: “I would I had that corporal soundness”: Pervez Rizvi's Analysis of the Word Adjacency Network Method of Authorship Attribution
“I would I had that corporal soundness”: Pervez Rizvi's Analysis of the Word Adjacency Network Method of Authorship Attribution Open
In his two-part article ‘An Analysis of the Word Adjacency Network Method—Part 1—The evidence of its unsoundness’ and ‘Part 2—A true understanding of the method’ Digital Scholarship in the Humanities, 38: 347-78 (2022), Pervez Rizvi attemp…
View article: Joint Resource Scheduling for AMR Navigation Over Wireless Edge Networks
Joint Resource Scheduling for AMR Navigation Over Wireless Edge Networks Open
The future of autonomous systems will rely on the usage of wireless time-sensitive networks to connect mobile cyberphysical systems, such as Autonomous Mobile Robots (AMRs), to Edge compute platforms to offload computationally intensive wo…
View article: A State-Augmented Approach for Learning Optimal Resource Management Decisions in Wireless Networks
A State-Augmented Approach for Learning Optimal Resource Management Decisions in Wireless Networks Open
We consider a radio resource management (RRM) problem in a multi-user wireless network, where the goal is to optimize a network-wide utility function subject to constraints on the ergodic average performance of users. We propose a state-au…
View article: Learning Resilient Radio Resource Management Policies with Graph Neural Networks
Learning Resilient Radio Resource Management Policies with Graph Neural Networks Open
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. To achieve a …
View article: Communication-Control Co-design in Wireless Edge Industrial Systems
Communication-Control Co-design in Wireless Edge Industrial Systems Open
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. The wireless control system model supports …
View article: Large-Scale Graph Reinforcement Learning in Wireless Control Systems
Large-Scale Graph Reinforcement Learning in Wireless Control Systems Open
Modern control systems routinely employ wireless networks to exchange information between spatially distributed plants, actuators and sensors. With wireless networks defined by random, rapidly changing transmission conditions that challeng…
View article: Learning Decentralized Wireless Resource Allocations With Graph Neural Networks
Learning Decentralized Wireless Resource Allocations With Graph Neural Networks Open
We consider the broad class of decentralized optimal resource allocation\nproblems in wireless networks, which can be formulated as a constrained\nstatistical learning problems with a localized information structure. We\ndevelop the use of…
View article: State-Augmented Learnable Algorithms for Resource Management in Wireless Networks
State-Augmented Learnable Algorithms for Resource Management in Wireless Networks Open
We consider resource management problems in multi-user wireless networks,\nwhich can be cast as optimizing a network-wide utility function, subject to\nconstraints on the long-term average performance of users across the network.\nWe propo…
View article: Stable and Transferable Wireless Resource Allocation Policies via Manifold Neural Networks
Stable and Transferable Wireless Resource Allocation Policies via Manifold Neural Networks Open
We consider the problem of resource allocation in large scale wireless networks. When contextualizing wireless network structures as graphs, we can model the limits of very large wireless systems as manifolds. To solve the problem in the m…
View article: Unsupervised Learning for Asynchronous Resource Allocation in Ad-hoc Wireless Networks
Unsupervised Learning for Asynchronous Resource Allocation in Ad-hoc Wireless Networks Open
We consider optimal resource allocation problems under asynchronous wireless network setting. Without explicit model knowledge, we design an unsupervised learning method based on Aggregation Graph Neural Networks (Agg-GNNs). Depending on t…
View article: Resource Allocation via Model-Free Deep Learning in Free Space Optical Networks.
Resource Allocation via Model-Free Deep Learning in Free Space Optical Networks. Open
This paper investigates the general problem of resource allocation for mitigating channel fading effects in Free Space Optical (FSO) networks. The resource allocation problem is modelled with a constrained stochastic optimization framework…
View article: Resource Allocation via Model-Free Deep Learning in Free Space Optical Communications
Resource Allocation via Model-Free Deep Learning in Free Space Optical Communications Open
This paper investigates the general problem of resource allocation for mitigating channel fading effects in Free Space Optical (FSO) communications. The resource allocation problem is modeled as the constrained stochastic optimization fram…
View article: Resource Allocation via Graph Neural Networks in Free Space Optical Fronthaul Networks
Resource Allocation via Graph Neural Networks in Free Space Optical Fronthaul Networks Open
This paper investigates the optimal resource allocation in free space optical (FSO) fronthaul networks. The optimal allocation maximizes an average weighted sum-capacity subject to power limitation and data congestion constraints. Both ada…
View article: Control-Aware Scheduling for Low Latency Wireless Systems with Deep Learning
Control-Aware Scheduling for Low Latency Wireless Systems with Deep Learning Open
We consider the problem of scheduling transmissions over low-latency wireless communication links to control various control systems. Low-latency requirements are critical in developing wireless technology for industrial control and Tactil…
View article: Scheduling Low Latency Traffic for Wireless Control Systems in 5G Networks
Scheduling Low Latency Traffic for Wireless Control Systems in 5G Networks Open
We consider the problem of allocating 5G radio resources over wireless communication links to control a series of independent low-latency wireless control systems common in industrial settings. Each control system sends state information t…
View article: Wireless Power Control via Counterfactual Optimization of Graph Neural Networks
Wireless Power Control via Counterfactual Optimization of Graph Neural Networks Open
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. To mitigate the interference among concurrent tra…
View article: A Response to Rosalind Barber’s Critique of the Word Adjacency Method for Authorship Attribution
A Response to Rosalind Barber’s Critique of the Word Adjacency Method for Authorship Attribution Open
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
View article: Model-Free Learning of Optimal Ergodic Policies in Wireless Systems
Model-Free Learning of Optimal Ergodic Policies in Wireless Systems Open
Learning optimal resource allocation policies in wireless systems can be\neffectively achieved by formulating finite dimensional constrained programs\nwhich depend on system configuration, as well as the adopted learning\nparameterization.…
View article: Resource Allocation in Large-Scale Wireless Control Systems with Graph Neural Networks
Resource Allocation in Large-Scale Wireless Control Systems with Graph Neural Networks Open
Modern control systems routinely employ wireless networks to exchange information between a large number of plants, actuators and sensors. While wireless networks are defined by random, rapidly changing conditions that challenge common con…
View article: Optimal Wireless Resource Allocation With Random Edge Graph Neural Networks
Optimal Wireless Resource Allocation With Random Edge Graph Neural Networks Open
We consider the problem of optimally allocating resources across a set of\ntransmitters and receivers in a wireless network. The resulting optimization\nproblem takes the form of constrained statistical learning, in which solutions\ncan be…
View article: A Primal-Dual Quasi-Newton Method for Exact Consensus Optimization
A Primal-Dual Quasi-Newton Method for Exact Consensus Optimization Open
We introduce the primal-dual quasi-Newton (PD-QN) method as an approximated\nsecond order method for solving decentralized optimization problems. The PD-QN\nmethod performs quasi-Newton updates on both the primal and dual variables of\nthe…
View article: Optimal Resource Allocation in Wireless Control Systems via Deep Policy Gradient
Optimal Resource Allocation in Wireless Control Systems via Deep Policy Gradient Open
In wireless control systems, remote control of plants is achieved through closing of the control loop over a wireless channel. As wireless communication is noisy and subject to packet dropouts, proper allocation of limited resources, e.g. …
View article: Optimal WDM Power Allocation via Deep Learning for Radio on Free Space Optics Systems
Optimal WDM Power Allocation via Deep Learning for Radio on Free Space Optics Systems Open
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. This paper investigates the optimal design …
View article: Control Aware Radio Resource Allocation in Low Latency Wireless Control Systems
Control Aware Radio Resource Allocation in Low Latency Wireless Control Systems Open
We consider the problem of allocating radio resources over wireless communication links to control a series of independent wireless control systems. Low-latency transmissions are necessary in enabling time-sensitive control systems to oper…
View article: Learning Optimal Resource Allocations in Wireless Systems
Learning Optimal Resource Allocations in Wireless Systems Open
This paper considers the design of optimal resource allocation policies in\nwireless communication systems which are generically modeled as a functional\noptimization problem with stochastic constraints. These optimization problems\nhave t…
View article: A Response to Pervez Rizvi’s Critique of the Word Adjacency Method for Authorship Attribution
A Response to Pervez Rizvi’s Critique of the Word Adjacency Method for Authorship Attribution Open
Pervez Rizvi recently gave a critique of the Word Adjacency Network method for authorship attribution developed by the present authors. The two publications of ours that Rizvi explicitly addresses ...
View article: Learning in Wireless Control Systems Over Nonstationary Channels
Learning in Wireless Control Systems Over Nonstationary Channels Open
This paper considers a set of multiple independent control systems that are\neach connected over a non-stationary wireless channel. The goal is to maximize\ncontrol performance over all the systems through the allocation of transmitting\np…
View article: IQN: An Incremental Quasi-Newton Method with Local Superlinear Convergence Rate
IQN: An Incremental Quasi-Newton Method with Local Superlinear Convergence Rate Open
The problem of minimizing an objective that can be written as the sum of a set of $n$ smooth and strongly convex functions is considered. The Incremental Quasi-Newton (IQN) method proposed here belongs to the family of stochastic and incre…