Accelerated linear convergence of stochastic momentum methods in wasserstein distances B Can, M Gurbuzbalaban, L Zhu International Conference on Machine Learning, 891-901, 2019 | 41 | 2019 |
Ideal: Inexact decentralized accelerated augmented lagrangian method Y Arjevani, J Bruna, B Can, M Gurbuzbalaban, S Jegelka, H Lin Advances in Neural Information Processing Systems 33, 20648-20659, 2020 | 24 | 2020 |
Entropic risk-averse generalized momentum methods B Can, M Gürbüzbalaban arXiv preprint arXiv:2204.11292, 2022 | 6 | 2022 |
Tengrad: Time-efficient natural gradient descent with exact fisher-block inversion S Soori, B Can, B Mu, M Gürbüzbalaban, MM Dehnavi arXiv preprint arXiv:2106.03947, 2021 | 6 | 2021 |
ASYNC: A cloud engine with asynchrony and history for distributed machine learning S Soori, B Can, M Gurbuzbalaban, MM Dehnavi 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2020 | 6 | 2020 |
Conditional law and occupation times of two-sided sticky Brownian motion B Can, M Çağlar Statistics & Probability Letters 165, 108856, 2020 | 5 | 2020 |
HyLo: a hybrid low-rank natural gradient descent method B Mu, S Soori, B Can, M Gürbüzbalaban, MM Dehnavi SC22: International Conference for High Performance Computing, Networking …, 2022 | 4 | 2022 |
A Variance-Reduced Stochastic Accelerated Primal Dual Algorithm B Can, M Gurbuzbalaban, NS Aybat arXiv preprint arXiv:2202.09688, 2022 | 3 | 2022 |
Randomized gossiping with effective resistance weights: Performance guarantees and applications B Can, S Soori, NS Aybat, MM Dehnavi, M Gürbüzbalaban IEEE Transactions on Control of Network Systems 9 (2), 524-536, 2022 | 2 | 2022 |
Decentralized computation of effective resistances and acceleration of distributed optimization algorithms. arXiv e-print B Can, S Soori, NS Aybat, MM Dehvani, M Gürbüzbalaban arXiv preprint arXiv:1907.13110, 2019 | 2 | 2019 |
L-DQN: An asynchronous limited-memory distributed Quasi-Newton method B Can, S Soori, MM Dehnavi, M Gürbüzbalaban 2021 60th IEEE Conference on Decision and Control (CDC), 2386-2393, 2021 | 1 | 2021 |
Theory and methods for stochastic, accelerated, and distributed optimization B Can Rutgers The State University of New Jersey, Graduate School-Newark, 2022 | | 2022 |
ASYNC: Asynchronous Machine Learning on Distributed Systems. S Soori, B Can, M Gurbuzbalaban, MM Dehnavi arXiv preprint arXiv:1907.08526, 2019 | | 2019 |
Multigroup SIS Epidemics With Simplicial and Higher Order Interactions..... P. Cisneros-Velarde and F. Bullo 695 B Can, S Soori, NS Aybat, MM Dehnavi, M Gürbüzbalaban, Y Bi, J Lavaei, ... | | |