Publications

Journal and Preprints

  1. Graph-Theoretic Analysis of Belief System Dynamics under Logic Constraints 
    A. Nedić, A. Olshevsky, and C. A. Uribe
    Scientific Reports 9 (1), 8843 , 2019
  2. Fast Convergence Rates for Distributed Non-Bayesian Learning
    A. Nedić, A. Olshevsky, and C. A. Uribe
    IEEE Transactions on Automatic Control  vol. 62, no. 11, pp. 5538-5553, 2017
  3. Optimal Distributed Optimization on Slowly Time-Varying Graphs
    A. Rogozin, C.A. Uribe, A. Gasnikov, N. Malkovsky, A. Nedić
    IEEE Transactions on Control of Network Systems vol. 7, no. 2, pp. 829-841, 2020
  4. A Dual Approach for Optimal Algorithms in Distributed Optimization over Networks
    C. A. Uribe, S. Lee, A. Gasnikov and A. Nedić
    Optimization Methods and Software, 2020
  5. Accelerating incremental gradient optimization with curvature information
    H.T. Wai, W. Shi, C.A. Uribe, A. Nedić, A. Scaglione
    Computational Optimization and Applications vol 76, pp. 347–380, 2020
  6. Robust Optimization over Networks Using Distributed Restarting of Accelerated Dynamics
    D. E. Ochoa, J.I. Poveda, C.A. Uribe, N. Quijano
    IEEE Control Systems Letters, 2020
  7. Non-Bayesian social learning with uncertain models
    J. Z. Hare, C. A. Uribe, L. Kaplan, and A. Jadbabaie
    IEEE Transactions on Signal Processing, to appear
  8. Resilient Primal-Dual Optimization Algorithms for Distributed Resource Allocation
    B. Turan, C.A. Uribe, H.-T. Wai, and M. Alizadeh
    IEEE Transactions on Control of Network Systems, 2020 (Accepted)
  9. Generalized self-concordant Hessian-barrier algorithms
    P. Dvurechensky, M. Staudigl, and C. A. Uribe
    Submitted
  10. Distributed Learning for Cooperative Inference
    A. Nedić, A. Olshevsky, and C. A. Uribe
    Submitted
  11. Near-optimal tensor methods for minimizing gradient norm
    P. Dvurechensky, A. Gasnikov, P. Ostroukhov, C. A. Uribe, and A. Ivanova
    Submitted

Machine Learning Theory Conference Papers

  1. A Distributed Cubic-Regularized Newton Method for Smooth Convex Optimization over Networks
    C. A. Uribe, Ali Jadbabaie
  2. Optimal Tensor Methods in Smooth Convex and Uniformly Convex Optimization
    A. Gasnikov, P. Dvurechensky, E. Gorbunov, E. Vorontsova, D. Selikhanovych, C. A. Uribe
    COLT 2019
  3. On the Complexity of Approximating Wasserstein Barycenters
    A. Kroshnin, D. Dvinskikh, P. Dvurechensky, A. Gasnikov, N. Tupitsa, C.A. Uribe
    ICML 2019.
  4. Decentralize and Randomize: Faster Algorithm for Wasserstein Barycenters
    P. Dvurechensky, D. Dvinskikh, A. Gasnikov, C.A. Uribe, and A. Nedić
    NeurIPS 2018 (Spotlight: Top 4% of the submitted papers)

Control Theory Conference Papers

  1. On Robustness of the Normalized Subgradient Method with Randomly Corrupted Subgradients
    Berkay Turan, C.A. Uribe, Hoi-To Wai, Mahnoosh Alizadeh
    Submitted American Control Conference (ACC), 2021.
  2. Robust Asynchronous and Network-Independent Cooperative Learning
    E. Mojica-Nava, D. Yanguas-Rojas, C.A. Uribe
    Submitted American Control Conference (ACC), 2021.
  3. Non-Bayesian Social Learning with Gaussian Uncertain Models
    J. Z. Hare, C.A. Uribe, L. Kaplan, and A. Jadbabaie
    American Control Conference (ACC), 2020.
  4. Resilient Distributed Optimization Algorithms for Resource Allocation
    C.A. Uribe, H.T. Wai, M. Alizadeh
    IEEE Control and Decision Conference (CDC), 2019.
  5. Non-Bayesian Social Learning with Uncertain Models over Time-Varying Directed Graphs
    C.A. Uribe, J. Hare, L. Kaplan, A. Jadbabaie
    IEEE Control and Decision Conference (CDC), 2019..
  6. Hybrid Robust Optimal Resource Allocation with Momentum
    D. Ochoa, J.I. Poveda, C.A. Uribe, N. Quijano
    IEEE Control and Decision Conference (CDC), 2019.
  7. On Primal and Dual Approaches for Distributed Stochastic Convex Optimization over Networks
    D. Dvinskikh, E. Gorbunov, A. Gasnikov, P. Dvurechensky, C.A. Uribe
    IEEE Control and Decision Conference (CDC), 2019..
  8. On Increasing Self-Confidence in Non-Bayesian Social Learning over Time-Varying Directed Graphs
    C.A. Uribe, and A. Jadbabaie
    American Control Conference (ACC), 2019.
  9. Achieving Acceleration in Distributed Optimization via Direct Discretization of the Heavy-Ball ODE
    J. Zhang, C.A. Uribe, A. Mokhtari, and A. Jadbabaie
    American Control Conference (ACC), 2019.
  10. A Method for Distributed Transactive Control in Power Systems based on the Projected Consensus Algorithm
    E. Baron-Prada, C.A. Uribe, and E. Mojica-Nava
    NecSys 2018.
  11. Distributed Computation of Wasserstein Barycenters over Networks
    C.A. Uribe, D. Dvinskikh, P. Dvurechensky, A. Gasnikov, and A. Nedić
    IEEE Control and Decision Conference (CDC), 2018.
  12. Geometrically Convergent Distributed Optimization with Uncoordinated Step-Sizes
    A. Nedić, A. Olshevsky, W.Shi, and C. A. Uribe
    American Control Conference (ACC), 2017.
  13. A Tutorial on Distributed (Non-Bayesian) Learning: Problem, Algorithms and Results
    A. Nedić, A. Olshevsky, and C. A. Uribe
    IEEE Control and Decision Conference (CDC), 2016.
  14. Distributed Learning with Infinitely Many Hypotheses
    A. Nedić, A. Olshevsky, and C. A. Uribe
    IEEE Control and Decision Conference (CDC), 2016.
  15. Network Independent Rates in Distributed Learning
    A. Nedić, A. Olshevsky, and C. A. Uribe
    American Control Conference (ACC), 2016. Best Presentation in the Learning and Estimation in Networks Session.
  16. Nonasymptotic Convergence Rates for Cooperative Learning Over Time-Varying Directed Graphs
    A. Nedić, A. Olshevsky, and C. A. Uribe
    American Control Conference (ACC), 2015.
  17. Computing Optimal Control Laws for Finite Stochastic Systems with Non-Classical Information Patterns.
    C. A. Uribe, T. Keviczky, and J. H. van Schuppen.
    American Control Conference (ACC), 2014, Best Presentation in the Decentralized Control Session.
  18. Analysis of Signaling in a Finite Stochastic System Motivated by Decentralized Control.
    C. A. Uribe, and J. H. van Schuppen
    IEEE Control and Decision Conference (CDC), 2013

Signal Processing Conference Papers

  1. Communication Constrained Learning with Uncertain Models
    J. Hare, C.A. Uribe, L. Kaplan, A. Jadbabaie
    ICASSP, 2020.
  2. On Malicious Agents in Non-Bayesian Social Learning Theory with Uncertain Model
    J. Hare, C.A. Uribe, L. Kaplan, A. Jadbabaie
    FUSION 2019.
  3. Distributed Gaussian Learning over Time-varying Directed Graphs
    A. Nedić, A. Olshevsky, and C. A. Uribe
    Asilomar Conference on Signals, Systems, and Computers, 2016.

Book Chapters

  1. Gradient Method for Problems with Inexact Model of the Objective
    F. Stonyakin, D. Dvinskikh, P. Dvurechensky, A. Kroshnin, O. Kuznetsova, A. Agafonov, A. Gasnikov, A. Turin, C.A. Uribe, D. Pasechnyuk and S. Artamonov
    MOTOR 2019, Springer Nature – Lecture Notes in Computer Science (LNCS).
  2. Signaling of Information.
    C. A. Uribe, and J. H. van Schuppen.
    Coordination Control of Distributed Systems, Lecture Notes Series Control and Information Sciences (LNCIS), Springer, 2014.
  3. Unsupervised feature selection based on fuzzy clustering for fault detection of the Tennessee Eastman process.
    C. Bedoya, C. Uribe, and C. Isaza.
    13th Ibero-American Conference on AI (IBERAMIA). Lecture Notes in Computer Science, Springer, 2012.

Others (Published while Undergraduate)

  1. Unsupervised feature selection based on fuzzy partition optimization for industrial processes monitoring.
    C. Uribe and C. Isaza.
    IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA), 2011.
  2. Qualitative-fuzzy decision support system for monitoring patients with cardiovascular risk.
    C. Uribe, C. Isaza, and J. Florez-Arango.
    IEEE Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 2011.
  3. A wrapper approach based on clustering for sensors selection of industrial monitoring systems.
    C. Uribe, C. Isaza, O. Gualdron, C. Duran, and A. Carvajal.
    International Conference on Broadband, Wireless Computing, Communication and Applications (BWCCA), 2010.
  4. Expert knowledge-guided feature selection for data-based industrial process monitoring.
    C. Uribe, and C. Isaza.
    Revista Facultad Ingeniería Universidad de Antioquia N.° 65, 2012.
  5. Fast Variable Selection Based on Stochastic Methods (Simulated Annealing) Coupled to Least Square Support Vector Machines: Application to Multisensor System (In Spanish)
    O. Gualdron, C. Duran, C. Isaza, A. Carvajal, and C. Uribe.
    VIII Congreso Internacional Electrónica y Tecnologías de Avanzada, 2011.
  6. Low Cost Electronic Nose System for Detecting Different Chemicals Pollutants (In Spanish).
    C. Duran, O. Gualdron, C. Isaza, A. Carvajal and C. Uribe.
    Revista Colombiana de Tecnologías de Avanzada, 2011.
  7. Data Acquisition, Analysis and Processing Tool for Multisensory Systems and Mass Spectrometry” (In Spanish).
    C. Duran, O. Gualdron, C. Isaza, A. Carvajal, and C. Uribe.
    7th International Congress of Electrical Electronic and Systems Engineering, (INTERCON), 2010.
  8. Integration methodology of face detection and speech recognition.
    C. Uribe, and C. Isaza.
    International Conference on Image Processing, Computer Vision, & Pattern Recognition, (IPCV), 2009.
  9. High School Robotics as a Research Skills developing process. (In Spanish).
    C. Uribe, and O. Carrillo, D. Fernandez.
    Sixth World Congress of Scientific Youth, International Federation of Scientific Societies, 2009.
  10. Algoritmo de Ubicación y Conducta en Entornos Conocidos con Condiciones Iniciales Desconocidas (In Spanish).
    C. Uribe, J. Marín, A. Pedraza, L. Arango, and C. Madrigal.
    CINTEX Journal, Vol. 13. 2008.