Stebėti
César A. Uribe
Pavadinimas
Cituota
Cituota
Metai
Fast convergence rates for distributed non-Bayesian learning
A Nedić, A Olshevsky, CA Uribe
IEEE Transactions on Automatic Control, 2017
2242017
A dual approach for optimal algorithms in distributed optimization over networks
CA Uribe, S Lee, A Gasnikov, A Nedić
Optimization Methods and Software, 1-40, 2020
223*2020
Geometrically convergent distributed optimization with uncoordinated step-sizes
A Nedić, A Olshevsky, W Shi, CA Uribe
American Control Conference (ACC), 2017, 3950-3955, 2017
1782017
Decentralize and randomize: Faster algorithm for Wasserstein barycenters
P Dvurechenskii, D Dvinskikh, A Gasnikov, C Uribe, A Nedich
Advances in Neural Information Processing Systems, 10783-10793, 2018
1272018
On the complexity of approximating Wasserstein barycenters
A Kroshnin, N Tupitsa, D Dvinskikh, P Dvurechensky, A Gasnikov, C Uribe
International Conference on Machine Learning, 3530-3540, 2019
1222019
Nonasymptotic convergence rates for cooperative learning over time-varying directed graphs
A Nedić, A Olshevsky, CA Uribe
2015 American Control Conference (ACC), 5884-5889, 2015
1062015
Near Optimal Methods for Minimizing Convex Functions with Lipschitz -th Derivatives
A Gasnikov, P Dvurechensky, E Gorbunov, E Vorontsova, ...
Conference on Learning Theory, 1392-1393, 2019
882019
Optimal Tensor Methods in Smooth Convex and Uniformly Convex Optimization
A Gasnikov, P Dvurechensky, E Gorbunov, E Vorontsova, ...
Conference on Learning Theory, 1374-1391, 2019
79*2019
Gradient methods for problems with inexact model of the objective
FS Stonyakin, D Dvinskikh, P Dvurechensky, A Kroshnin, O Kuznetsova, ...
Mathematical Optimization Theory and Operations Research: 18th International …, 2019
632019
Distributed computation of Wasserstein barycenters over networks
CA Uribe, D Dvinskikh, P Dvurechensky, A Gasnikov, A Nedić
2018 IEEE Conference on Decision and Control (CDC), 6544-6549, 2018
582018
On Primal and Dual Approaches for Distributed Stochastic Convex Optimization over Networks
D Dvinskikh, E Gorbunov, A Gasnikov, P Dvurechensky, CA Uribe
2019 IEEE 58th Conference on Decision and Control (CDC), 7435-7440, 2019
43*2019
A tutorial on distributed (non-Bayesian) learning: Problem, algorithms and results
A Nedić, A Olshevsky, CA Uribe
Decision and Control (CDC), 2016 IEEE 55th Conference on, 6795-6801, 2016
412016
Nonasymptotic Concentration Rates in Cooperative Learning–Part I: Variational Non-Bayesian Social Learning
CA Uribe, A Olshevsky, A Nedić
IEEE Transactions on Control of Network Systems 9 (3), 1128-1140, 2022
40*2022
Resilient primal–dual optimization algorithms for distributed resource allocation
B Turan, CA Uribe, HT Wai, M Alizadeh
IEEE Transactions on Control of Network Systems 8 (1), 282-294, 2020
382020
Optimal distributed convex optimization on slowly time-varying graphs
A Rogozin, CA Uribe, AV Gasnikov, N Malkovsky, A Nedić
IEEE Transactions on Control of Network Systems 7 (2), 829-841, 2019
382019
Multimarginal optimal transport by accelerated alternating minimization
N Tupitsa, P Dvurechensky, A Gasnikov, CA Uribe
2020 59th IEEE Conference on Decision and Control (CDC), 6132-6137, 2020
282020
Non-Bayesian social learning with uncertain models
JZ Hare, CA Uribe, L Kaplan, A Jadbabaie
IEEE Transactions on Signal Processing 68, 4178-4193, 2020
262020
Accelerating incremental gradient optimization with curvature information
HT Wai, W Shi, CA Uribe, A Nedić, A Scaglione
Computational Optimization and Applications 76 (2), 347-380, 2020
26*2020
Network independent rates in distributed learning
A Nedić, A Olshevsky, C Uribe
2016 American Control Conference (ACC), 1072-1077, 2016
252016
Achieving acceleration in distributed optimization via direct discretization of the heavy-ball ODE
J Zhang, CA Uribe, A Mokhtari, A Jadbabaie
2019 American Control Conference (ACC), 3408-3413, 2019
232019
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Straipsniai 1–20