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Found 8 papers, 0 papers with code
Human-in-the-loop Learning for Dynamic Congestion Games
To address this, we focus on informational (non-monetary) mechanisms as they are easier to implement than pricing.
Incentivizing Massive Unknown Workers for Budget-Limited Crowdsensing: From Off-Line and On-Line Perspectives
How to incentivize strategic workers using limited budget is a very fundamental problem for crowdsensing systems; nevertheless, since the sensing abilities of the workers may not always be known as prior knowledge due to the diversities of their sensor devices and behaviors, it is difficult to properly select and pay the unknown workers.
Multi-Objective Optimization for UAV Swarm-Assisted IoT with Virtual Antenna Arrays
The existing UAV-assisted data harvesting and dissemination schemes largely require UAVs to frequently fly between the IoTs and access points, resulting in extra energy and time costs.
Adaptive Federated Learning via New Entropy Approach
In this paper, by leveraging entropy as a new metric for assessing the degree of system disorder, we propose an adaptive FEDerated learning algorithm based on ENTropy theory (FedEnt) to alleviate the parameter deviation among heterogeneous clients and achieve fast convergence.
Regulating Clients' Noise Adding in Federated Learning without Verification
In federated learning (FL), clients cooperatively train a global model without revealing their raw data but gradients or parameters, while the local information can still be disclosed from local outputs transmitted to the parameter server.
Online Pricing Incentive to Sample Fresh Information
To motivate drivers to route and sample diverse paths, this paper is the first to propose online pricing for a provider to economically reward drivers for diverse routing and control the actual AoI dynamics over time and spatial path domains.
Dynamic Pricing and Mean Field Analysis for Controlling Age of Information
This dynamic pricing design problem needs to well balance the monetary payments as rewards to users and the AoI evolution over time, and is challenging to solve especially under the incomplete information about users' arrivals and their private sampling costs.
Multi-UAV Cooperative Trajectory for Servicing Dynamic Demands and Charging Battery
To our best knowledge, this paper is the first to design and analyze cooperative path planning algorithms of a large UAV swarm for optimally servicing many spatial locations, where ground users' demands are released dynamically in the long time horizon.
Networking and Internet Architecture
