Mitigating Data Heterogeneity in Federated Learning with Data Augmentation. - Artur Back de Luca; Guojun Zhang; Xi Chen; Yaoliang Yu (CoRR, 2022)

Local Graph Clustering with Noisy Labels. - Artur Back de Luca; Kimon Fountoulakis; Shenghao Yang 002 (ICLR, 2024)

Simulation of Graph Algorithms with Looped Transformers. - Artur Back de Luca; Kimon Fountoulakis (ICML, 2024)

Positional Attention: Out-of-Distribution Generalization and Expressivity for Neural Algorithmic Reasoning. - Artur Back de Luca; George Giapitzakis; Shenghao Yang 002; Petar Velickovic; Kimon Fountoulakis (CoRR, 2024)

Exact Learning of Permutations for Nonzero Binary Inputs with Logarithmic Training Size and Quadratic Ensemble Complexity. - George Giapitzakis; Artur Back de Luca; Kimon Fountoulakis (CoRR, 2025)