Publications by Valentina Shumovskaia

Social Learning in Community Structured Graphs

Ali H. Sayed, Mert Kayaalp, Valentina Shumovskaia

Traditional social learning frameworks consider environments with a homogeneous state, where each agent receives observations conditioned on that true state of nature. In this work, we relax this assumption and study the distributed hypothesis testing prob ...

2024

Detection of Malicious Agents in Social Learning

Ali H. Sayed, Mert Kayaalp, Valentina Shumovskaia

Non-Bayesian social learning is a framework for distributed hypothesis testing aimed at learning the true state of the environment. Traditionally, the agents are assumed to receive observations conditioned on the same true state, although it is also possib ...

IEEE Institute of Electrical and Electronics Engineers2024

Distributed Decision-Making for Community Structured Networks

Ali H. Sayed, Mert Kayaalp, Valentina Shumovskaia

Traditional social learning frameworks consider environments with a homogeneous state where each agent receives observations conditioned on the same hypothesis. In this work, we study the distributed hypothesis testing problem for graphs with a community s ...

Institute of Electrical and Electronics Engineers Inc.2024

Inverse Graph Learning from Social Interactions

Valentina Shumovskaia

The social learning paradigm for distributed hypothesis testing involves a collection of agents interacting over a graph, each observing streaming data that provide evidence about the state of the environment. These agents perform a series of local Bayesia ...

EPFL2024

Discovering Influencers in Opinion Formation Over Social Graphs

Ali H. Sayed, Mert Kayaalp, Valentina Shumovskaia, Mert Cemri

The adaptive social learning paradigm helps model how networked agents are able to form opinions on a state of nature and track its drifts in a changing environment. In this framework, the agents repeatedly update their beliefs based on private observation ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Asynchronous Social Learning

Ali H. Sayed, Virginia Bordignon, Mert Kayaalp, Valentina Shumovskaia

Social learning algorithms provide a model for the formation and propagation of opinions over social networks. However, most studies focus on the case in which agents share their information synchronously over regular intervals. In this work, we analyze be ...

IEEE2023

Explainability and Graph Learning From Social Interactions

Ali H. Sayed, Stefan Vlaski, Konstantinos Ntemos, Valentina Shumovskaia

Social learning algorithms provide models for the formation of opinions over social networks resulting from local reasoning and peer-to-peer exchanges. Interactions occur over an underlying graph topology, which describes the flow of information among the ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022