César A. Uribe

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Angelia NedichProfessor, Arizona State UniversityVerified email at asu.edu
Alexander GasnikovMIPTVerified email at mipt.ru
Pavel DvurechenskyWeierstrass Institute for Applied Analysis and StochasticsVerified email at wias-berlin.de
Alex OlshevskyAssociate Professor, Boston UniversityVerified email at bu.edu
Darina DvinskikhHSE UniversityVerified email at hse.ru
Ali JadbabaieJR East Professor of Engineering, MITVerified email at mit.edu
Soomin LeeAmazon Alexa Shopping ResearchVerified email at amazon.com
Eduard GorbunovPostdoctoral Fellow, Mohamed bin Zayed University of Artificial IntelligenceVerified email at mbzuai.ac.ae
Lance KaplanArmy Research LaboratoryVerified email at mail.mil
James Zachary HarePost Doctoral Fellow, Army Research LaboratoryVerified email at uconn.edu
Hoi-To WaiAssistant Professor, The Chinese University of Hong KongVerified email at se.cuhk.edu.hk
CLAUDIA VICTORIA ISAZA NARVAEZFull Professor, Universidad de AntioquiaVerified email at udea.edu.co
Taha ToghaniPh.D. Student, Rice UniversityVerified email at rice.edu
Evgeniya A. VorontsovaCatholic University of Louvain (UCL)Verified email at uclouvain.be
Daniil SelikhanovychSkolkovo Institute of Science and TechnologiesVerified email at phystech.edu
Wei (Wilbur) ShiPostdoctoral Research Associate, Princeton UniversityVerified email at princeton.edu
Alexey KroshninWIAS, IITP, HSEVerified email at wias-berlin.de
Mahnoosh AlizadehAssociate Professor of Electrical and Computer Engineering, University of California Santa BarbaraVerified email at ece.ucsb.edu
Berkay TuranPh.D. Candidate, University of California, Santa BarbaraVerified email at ucsb.edu
Jorge I. PovedaAssistant Professor, University of California, San DiegoVerified email at ucsd.edu

César A. Uribe

Rice University

Verified email at rice.edu - Homepage

Distributed Optimization Machine Learning Network Science Optimal Transport


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Fast convergence rates for distributed non-Bayesian learning A Nedić, A Olshevsky, CA Uribe IEEE Transactions on Automatic Control, 2017	172	2017
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	146	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	141	2017
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	104	2018
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	97	2019
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	93	2015
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	68	2019
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	62*	2019
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	58	2018
Optimal algorithms for distributed optimization CA Uribe, S Lee, A Gasnikov, A Nedić arXiv preprint arXiv:1712.00232, 2017	54	2017
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	52	2019
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	40*	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	34	2016
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	33	2019
Distributed Learning for Cooperative Inference A Nedić, A Olshevsky, CA Uribe arXiv preprint arXiv:1704.02718, 2017	27	2017
Network independent rates in distributed learning A Nedić, A Olshevsky, C Uribe 2016 American Control Conference (ACC), 1072-1077, 2016	25	2016
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	21	2020
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	21*	2020
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	19	2020
Unsupervised feature selection based on fuzzy clustering for fault detection of the Tennessee Eastman process C Bedoya, C Uribe, C Isaza Advances in Artificial Intelligence–IBERAMIA 2012, 350-360, 2012	19	2012

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