Publications (no priority list, rather random and quite unstructured)

2024/2025

• Pluvial Flood Emulation with Hydraulics-informed Message Passing, Arnold Kazadi, James Doss-Gollin, Arlei Silva, International Conference on Machine Learning (ICML), 2024.
• FloodGNN-GRU: A Spatio-Temporal Graph Neural Network for Flood Prediction, Arnold Kazadi, James Doss-Gollin, Antonia Sebastian, Arlei Silva, Environmental Data Science (EDS), 2024.
• Attribute-Enhanced Similarity Ranking for Sparse Link Prediction, Joao Mattos, Zexi Huang, Mert Kosan, Ambuj Singh, Arlei Silva, ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2025 (Accepted)
• Large-scale Collective Dynamics in the Three Iterations of the Reddit r/place Experiment, Yutong Wu, Arlei Silva, Preprint 2024, https://arxiv.org/abs/2408.13236
• Robust Online Selection with Uncertain Offer Acceptance, Perez-Salazar, Singh, Toriello (In Mathematics of Operations Research) https://pubsonline.informs.org/doi/abs/10.1287/moor.2023.0210
• Splitting Guarantees for Prophet Inequalities via Nonlinear Systems. Brustle, Perez-Salazar, Verdugo (To appear in the Proceedings of WINE 2024)
• Optimal Guarantees for Online Selection Over Time. Perez-Salazar, Verdugo (To appear in the Proceedings of WINE 2024).
• Fast fixmatch: Faster semi-supervised learning with curriculum batch size, J Chen, C Dun, A Kyrillidis, 2024 IEEE International Symposium on Information Theory (ISIT), 1836-1841
• A Catalyst Framework for the Quantum Linear System Problem via the Proximal Point Algorithm, JL Kim, NH Chia, A Kyrillidis, arXiv preprint arXiv:2406.13879
• On the Error-Propagation of Inexact Deflation for Principal Component Analysis, F Liao, JL Kim, C Barnum, A Kyrillidis, International Conference on Machine Learning (ICML), 2024.
• Sweeping heterogeneity with smart mops: Mixture of prompts for llm task adaptation, C Dun, MH Garcia, G Zheng, AH Awadallah, A Kyrillidis, R Sim, ΑΑΑΙ, 2025
• FedJETs: Efficient Just-In-Time Personalization with Federated Mixture of Experts, C Dun, MH Garcia, G Zheng, AH Awadallah, R Sim, A Kyrillidis, arXiv preprint arXiv:2306.08586
• Fair GLASSO: Estimating Fair Graphical Models with Unbiased Statistical Behavior, Madeline Navarro, Samuel Rey, Andrei Buciulea, Antonio G Marques, Santiago Segarra, NeurIPS (2024)
• Opportunities and challenges of graph neural networks in electrical engineering, Eli Chien, Mufei Li, Anthony Aportela, Kerr Ding, Shuyi Jia, Supriyo Maji, Zhongyuan Zhao, Javier Duarte, Victor Fung, Cong Hao, Yunan Luo, Olgica Milenkovic, David Pan, Santiago Segarra, Pan Li, Nature Reviews Electrical Engineering, vol. 1, no. 8, pp. 529-546 (2024).