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Found 8 papers, 1 papers with code
A Discrete-time Networked Competitive Bivirus SIS Model
We identify a sufficient condition for exponential convergence to the disease-free equilibrium (DFE).
Competitive Networked Bivirus SIS spread over Hypergraphs
The paper deals with the spread of two competing viruses over a network of population nodes, accounting for pairwise interactions and higher-order interactions (HOI) within and between the population nodes.
Towards Understanding the Endemic Behavior of a Competitive Tri-Virus SIS Networked Model
We also identify sufficient conditions for the existence of a 2-coexistence (resp.
On the Endemic Behavior of a Competitive Tri-Virus SIS Networked Model
This paper studies the endemic behavior of a multi-competitive networked susceptible-infected-susceptible (SIS) model.
Robust Distributed Optimization With Randomly Corrupted Gradients
In this paper, we propose a first-order distributed optimization algorithm that is provably robust to Byzantine failures-arbitrary and potentially adversarial behavior, where all the participating agents are prone to failure.
A General Framework for Distributed Inference with Uncertain Models
Non-Bayesian social learning theory provides a framework that solves this problem in an efficient manner by allowing the agents to sequentially communicate and update their beliefs for each hypothesis over the network.
Non-Bayesian Social Learning with Uncertain Models
Non-Bayesian social learning theory provides a framework that models distributed inference for a group of agents interacting over a social network.
Accelerating Incremental Gradient Optimization with Curvature Information
This paper studies an acceleration technique for incremental aggregated gradient ({\sf IAG}) method through the use of \emph{curvature} information for solving strongly convex finite sum optimization problems.
