César A. Uribe

Orcid: 0000-0002-7080-9724

Affiliations:
  • University of Illinois at Urbana-Champaign, Urbana, IL, USA


According to our database1, César A. Uribe authored at least 83 papers between 2009 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
A Moreau Envelope Approach for LQR Meta-Policy Estimation.
CoRR, 2024

Decentralized and Equitable Optimal Transport.
CoRR, 2024

PIDformer: Transformer Meets Control Theory.
CoRR, 2024

2023
PARS-Push: Personalized, Asynchronous and Robust Decentralized Optimization.
IEEE Control. Syst. Lett., 2023

Local Stochastic Factored Gradient Descent for Distributed Quantum State Tomography.
IEEE Control. Syst. Lett., 2023

A Discrete-time Networked Competitive Bivirus SIS Model.
CoRR, 2023

Competitive Networked Bivirus SIS spread over Hypergraphs.
CoRR, 2023

Adaptive Federated Learning with Auto-Tuned Clients.
CoRR, 2023

Towards Understanding the Endemic Behavior of a Competitive Tri-Virus SIS Networked Model.
CoRR, 2023

Multi-Competitive Virus Spread over a Time-Varying Networked SIS Model with an Infrastructure Network.
CoRR, 2023

On First-Order Meta-Reinforcement Learning with Moreau Envelopes.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

On the Performance of Gradient Tracking with Local Updates.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

On the Endemic Behavior of a Competitive Tri-Virus SIS Networked Model.
Proceedings of the American Control Conference, 2023

Improving Denoising Diffusion Probabilistic Models via Exploiting Shared Representations.
Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

2022
Robust Distributed Optimization With Randomly Corrupted Gradients.
IEEE Trans. Signal Process., 2022

Nonasymptotic Concentration Rates in Cooperative Learning - Part II: Inference on Compact Hypothesis Sets.
IEEE Trans. Control. Netw. Syst., 2022

Nonasymptotic Concentration Rates in Cooperative Learning-Part I: Variational Non-Bayesian Social Learning.
IEEE Trans. Control. Netw. Syst., 2022

Communication-Efficient Distributed Cooperative Learning With Compressed Beliefs.
IEEE Trans. Control. Netw. Syst., 2022

On arbitrary compression for decentralized consensus and stochastic optimization over directed networks.
Eur. J. Control, 2022

Hyperfast second-order local solvers for efficient statistically preconditioned distributed optimization.
EURO J. Comput. Optim., 2022

An energy management system model with power quality constraints for unbalanced multi-microgrids interacting in a local energy market.
CoRR, 2022

A State Feedback Controller for Mitigation of Continuous-Time Networked SIS Epidemics.
CoRR, 2022

PersA-FL: Personalized Asynchronous Federated Learning.
CoRR, 2022

Consensus ADMM-Based Distributed Simultaneous Imaging & Communication.
CoRR, 2022

The Role of Local Steps in Local SGD.
CoRR, 2022

Faster Convergence of Local SGD for Over-Parameterized Models.
CoRR, 2022

Approximate Wasserstein attraction flows for dynamic mass transport over networks.
Autom., 2022

On Acceleration of Gradient-Based Empirical Risk Minimization using Local Polynomial Regression.
Proceedings of the European Control Conference, 2022

Decentralized Federated Learning for Over-Parameterized Models.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022

On Distributed Exact Sparse Linear Regression over Networks.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Scalable Average Consensus with Compressed Communications.
Proceedings of the American Control Conference, 2022

Unbounded Gradients in Federated Learning with Buffered Asynchronous Aggregation.
Proceedings of the 58th Annual Allerton Conference on Communication, 2022

2021
A General Framework for Distributed Inference With Uncertain Models.
IEEE Trans. Signal Inf. Process. over Networks, 2021

Resilient Primal-Dual Optimization Algorithms for Distributed Resource Allocation.
IEEE Trans. Control. Netw. Syst., 2021

A dual approach for optimal algorithms in distributed optimization over networks.
Optim. Methods Softw., 2021

Robust Optimization Over Networks Using Distributed Restarting of Accelerated Dynamics.
IEEE Control. Syst. Lett., 2021

Computation-aware distributed optimization over networks: a hybrid dynamical systems approach.
Proceedings of the CAADCPS '21: Proceedings of the Workshop on Computation-Aware Algorithmic Design for Cyber-Physical Systems, 2021

On Robustness of the Normalized Random Block Coordinate Method for Non-Convex Optimization.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Communication-Efficient Decentralized Local SGD over Undirected Networks.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Toward Active Sequential Hypothesis Testing with Uncertain Models.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Application of Wasserstein Attraction Flows for Optimal Transport in Network Systems.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Model Reference Adaptive Control for Online Policy Adaptation and Network Synchronization.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

On Robustness of the Normalized Subgradient Method with Randomly Corrupted Subgradients.
Proceedings of the 2021 American Control Conference, 2021

Robust Asynchronous and Network-Independent Cooperative Learning.
Proceedings of the 2021 American Control Conference, 2021

Communication-Efficient and Fault-Tolerant Social Learning.
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

2020
Non-Bayesian Social Learning With Uncertain Models.
IEEE Trans. Signal Process., 2020

Optimal Distributed Convex Optimization on Slowly Time-Varying Graphs.
IEEE Trans. Control. Netw. Syst., 2020

A Distributed Cubic-Regularized Newton Method for Smooth Convex Optimization over Networks.
CoRR, 2020

Accelerating incremental gradient optimization with curvature information.
Comput. Optim. Appl., 2020

Communication Constrained Learning with Uncertain Models.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Multimarginal Optimal Transport by Accelerated Alternating Minimization.
Proceedings of the 59th IEEE Conference on Decision and Control, 2020

Non-Bayesian Social Learning with Gaussian Uncertain Models.
Proceedings of the 2020 American Control Conference, 2020

2019
Generalized Self-concordant Hessian-barrier algorithms.
CoRR, 2019

On the Complexity of Approximating Wasserstein Barycenter.
CoRR, 2019

Gradient Methods for Problems with Inexact Model of the Objective.
Proceedings of the Mathematical Optimization Theory and Operations Research, 2019

On the Complexity of Approximating Wasserstein Barycenters.
Proceedings of the 36th International Conference on Machine Learning, 2019

On Malicious Agents in Non-Bayesian Social Learning with Uncertain Models.
Proceedings of the 22th International Conference on Information Fusion, 2019

Optimal Tensor Methods in Smooth Convex and Uniformly ConvexOptimization.
Proceedings of the Conference on Learning Theory, 2019

Near Optimal Methods for Minimizing Convex Functions with Lipschitz $p$-th Derivatives.
Proceedings of the Conference on Learning Theory, 2019

Resilient Distributed Optimization Algorithms for Resource Allocation.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Non-Bayesian Social Learning with Uncertain Models over Time-Varying Directed Graphs.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Hybrid Robust Optimal Resource Allocation with Momentum.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

On Primal and Dual Approaches for Distributed Stochastic Convex Optimization over Networks.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Achieving Acceleration in Distributed Optimization via Direct Discretization of the Heavy-Ball ODE.
Proceedings of the 2019 American Control Conference, 2019

On Increasing Self-Confidence in Non-Bayesian Social Learning over Time-Varying Directed Graphs.
Proceedings of the 2019 American Control Conference, 2019

2018
Graph-Theoretic Analysis of Belief System Dynamics under Logic Constraints.
CoRR, 2018

Decentralize and Randomize: Faster Algorithm for Wasserstein Barycenters.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Distributed Computation of Wasserstein Barycenters Over Networks.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

2017
Fast Convergence Rates for Distributed Non-Bayesian Learning.
IEEE Trans. Autom. Control., 2017

Optimal Algorithms for Distributed Optimization.
CoRR, 2017

Distributed Learning for Cooperative Inference.
CoRR, 2017

Geometrically convergent distributed optimization with uncoordinated step-sizes.
Proceedings of the 2017 American Control Conference, 2017

2016
A tutorial on distributed (non-Bayesian) learning: Problem, algorithms and results.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

Distributed learning with infinitely many hypotheses.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

Network independent rates in distributed learning.
Proceedings of the 2016 American Control Conference, 2016

Distributed Gaussian learning over time-varying directed graphs.
Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

2015
Nonasymptotic convergence rates for cooperative learning over time-varying directed graphs.
Proceedings of the American Control Conference, 2015

2014
Computing optimal control laws for finite stochastic systems with non-classical information patterns.
Proceedings of the American Control Conference, 2014

2013
Analysis of signaling in a finite stochastic system motivated by decentralized control.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

2012
Unsupervised Feature Selection Based on Fuzzy Clustering for Fault Detection of the Tennessee Eastman Process.
Proceedings of the Advances in Artificial Intelligence - IBERAMIA 2012, 2012

2011
Qualitative-fuzzy decision support system for monitoring patients with cardiovascular risk.
Proceedings of the Eighth International Conference on Fuzzy Systems and Knowledge Discovery, 2011

2010
A Wrapper Approach Based on Clustering for Sensors Selection of Industrial Monitoring Systems.
Proceedings of the Fifth International Conference on Broadband and Wireless Computing, 2010

2009
Integration Methodology of Face Detection and Speech Recognition.
Proceedings of the 2009 International Conference on Image Processing, 2009


  Loading...