Accelerated Linear Convergence of Stochastic Momentum Methods in Wasserstein Distances. - Bugra Can; Mert Gürbüzbalaban; Lingjiong Zhu (ICML, 2019)

ASYNC: Asynchronous Machine Learning on Distributed Systems. - Saeed Soori; Bugra Can; Mert Gürbüzbalaban; Maryam Mehri Dehnavi (CoRR, 2019)

ASYNC: A Cloud Engine with Asynchrony and History for Distributed Machine Learning. - Saeed Soori; Bugra Can; Mert Gürbüzbalaban; Maryam Mehri Dehnavi (IPDPS, 2020)

IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method. - Yossi Arjevani; Joan Bruna; Bugra Can; Mert Gürbüzbalaban; Stefanie Jegelka; Hongzhou Lin (NeurIPS, 2020)

L-DQN: An Asynchronous Limited-Memory Distributed Quasi-Newton Method. - Bugra Can; Saeed Soori; Maryam Mehri Dehnavi; Mert Gürbüzbalaban (CDC, 2021)

TENGraD: Time-Efficient Natural Gradient Descent with Exact Fisher-Block Inversion. - Saeed Soori; Bugra Can; Baourun Mu; Mert Gürbüzbalaban; Maryam Mehri Dehnavi (CoRR, 2021)

HyLo: A Hybrid Low-Rank Natural Gradient Descent Method. - Baorun Mu; Saeed Soori; Bugra Can; Mert Gürbüzbalaban; Maryam Mehri Dehnavi (SC, 2022)

A Variance-Reduced Stochastic Accelerated Primal Dual Algorithm. - Bugra Can; Mert Gürbüzbalaban; Necdet Serhat Aybat (CoRR, 2022)

Randomized Gossiping With Effective Resistance Weights: Performance Guarantees and Applications. - Bugra Can; Saeed Soori; Necdet Serhat Aybat; Maryam Mehri Dehnavi; Mert Gürbüzbalaban (IEEE Trans. Control. Netw. Syst., 2022)

REACT: Residual-Adaptive Contextual Tuning for Fast Model Adaptation in Threat Detection. - Jiayun Zhang; Junshen Xu; Bugra Can; Yi Fan (WWW, 2025)