Valentina Shumovskaia

According to our database, Valentina Shumovskaia authored at least 12 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Social Learning in Community Structured Graphs.

Valentina Shumovskaia, Mert Kayaalp, Ali H. Sayed

IEEE Trans. Signal Process., 2024

Detection of Malicious Agents in Social Learning.

Valentina Shumovskaia, Mert Kayaalp, Ali H. Sayed

IEEE Signal Process. Lett., 2024

Distributed Decision-Making for Community Structured Networks.

Valentina Shumovskaia, Mert Kayaalp, Ali H. Sayed

Proceedings of the IEEE International Conference on Acoustics, 2024

2023

Identifying Opinion Influencers over Social Networks.

Valentina Shumovskaia, Mert Kayaalp, Ali H. Sayed

Proceedings of the IEEE International Conference on Acoustics, 2023

Asynchronous Social Learning.

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

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Explainability and Graph Learning From Social Interactions.

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

IEEE Trans. Signal Inf. Process. over Networks, 2022

Discovering Influencers in Opinion Formation over Social Graphs.

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

CoRR, 2022

How fair is your graph? Exploring fairness concerns in neuroimaging studies.

Fernanda Ribeiro, Valentina Shumovskaia, Thomas Davies, Ira Ktena

Proceedings of the Machine Learning for Healthcare Conference, 2022

2021

Linking bank clients using graph neural networks powered by rich transactional data.

Valentina Shumovskaia, Kirill Fedyanin, Ivan Sukharev, Dmitry Berestnev, Maxim Panov

Int. J. Data Sci. Anal., 2021

Online Graph Learning from Social Interactions.

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

Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

2020

EWS-GCN: Edge Weight-Shared Graph Convolutional Network for Transactional Banking Data.

Ivan Sukharev, Valentina Shumovskaia, Kirill Fedyanin, Maxim Panov, Dmitry Berestnev

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Linking Bank Clients using Graph Neural Networks Powered by Rich Transactional Data: Extended Abstract.

Valentina Shumovskaia, Kirill Fedyanin, Ivan Sukharev, Dmitry Berestnev, Maxim Panov

Proceedings of the 7th IEEE International Conference on Data Science and Advanced Analytics, 2020