Dr. Dušan Jakovetić

Title and affiliation

Associate Professor, Department of Mathematics and Informatics, Faculty of Sciences, University of Novi Sad, Novi Sad, Serbia

Email

               dusan.jakovetic@dmi.uns.ac.rs

Address

Department of Mathematics and Informatics, New Building, Second Floor, Room 1

Trg Dositeja Obradovica 3, 21000 Novi Sad, Serbia

Research interests

               Algorithms and systems for distributed optimization, inference, learning, and data analytics, and their applications.

Education

               Ph. D., Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA, 2013

               Ph. D., Instituto Superior Técnico, Lisbon, Portugal, 2013

               Dipl. Ing. (5 years degree), School of Electrical Engineering, University of Belgrade, 2007

Experience

               Associate Professor, Faculty of Sciences, University of Novi Sad, Serbia, 2020-present

Assistant Professor, Faculty of Sciences, University of Novi Sad, Serbia, 2015-2020

Visiting Researcher, University of Strathclyde, Glasgow, UK, June 2017-August 2017

Visiting Researcher, University of Ghent, Belgium, June 2015

               Senior Researcher, BioSense Institute, Novi Sad, Serbia, 2013-2015

               Postdoctoral Researcher, Instituto Superior Tecnico, Lisbon, Portugal, June 2013-October 2013

               Graduate Research Assistant (PhD student, Teaching Assistant), Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA, 2009-2011

               Graduate Research Assistant (PhD student), Instituto Superior Tecnico, Lisbon, Portugal, 2007-2009 + 2011-2013

Teaching

               Distributed optimization with applications (master-level; data science master program, https://www.pmf.uns.ac.rs/en/studies/study-programs/master-of-science-in-applied-mathematics-data-science/)

               Statistical theory for learning and signal processing (master-level; data science)

               Mathematical modeling seminar (master-level; data science and applied mathematics, https://www.dmi.uns.ac.rs/files/722/primenjena_matematika_mb.pdf)

               Signals and systems (master-level; data science)

               Network science (master-level; data science)

Projects

EU H2020 project “I-BiDaaS: Industrial-Driven Big Data as a Self-Service Solution”; duration: 2018-2020; scientific and technical coordinator

EU H2020 project “C4IIoT: Cyber security 4.0: protecting the Industrial Internet Of Things”; duration: 2019-2021; scientific and technical coordinator

EU H2020 project “COLLABS: A comprehensive cyber-intelligence framework for resilient collaborative manufacturing systems”; duration: 2020-2022; scientific and technical coordinator

EU H2020 project “BIGMATH: Big Data Challenges for Mathematics”; duration: 2018-2021; experienced researcher

EU H2020 project “ASCAPE: Artificial intelligence supporting cancer patients across Europe”; duration: 2020-2022; experienced researcher

EU H2020 project “CYRENE: Certifying the Security and Resilience of Supply Chain Services”; duration: 2020-2023; experienced researcher

“Probotain: An integrated predictive maintenance solution on robotic production line equipment”; subproject of EU H2020 project Market 4.0; duration: 2021-2022; experienced researcher

Interreg IPA Cross-border Cooperation program Croatia – Serbia project: “RealForAll: Real-time measurements and forecasting for successful prevention and management of seasonal allergies in Croatia-Serbia cross-border region”; duration 2017-2020; experienced researcher

“Application of optimization methods in biomedicine,” Serbia-Croatia Cooperation in Science and Technology; duration 2019-2020; (co-)coordinator

“Second Order Methods for Optimization Methods in Machine Learning,” Italia-Serbia Cooperation in Science and Technology, duration 2019-2022; experienced researcher

“Numerical methods, simulations, and applications”, Serbian Ministry of Education, Science, and Technological development; duration 2011-to date; experienced researcher

Awards

Dr. Zoran Djindjic special award for a young researcher with outstanding contributions to science in 2017, awarded by the Provincial Government of Vojvodina, Serbia; 2017

A. G. Milnes award, Carnegie Mellon University, Dept. of Electrical and Computer Engineering, “presented to an ECE doctoral student or students for Ph.D. thesis work judged to be of the highest quality and which is likely to have significant impact in his or her field;” 2014

Claire, MM 1965, and John Bertucci, E 1963, TPR 1965, Fellowship in Engineering, Carnegie Mellon University, Dept. of Electrical and Computer Engineering; 2012

Publications [selected]

Book chapters

 

·        A. Alexopoulos, Y. Becerra, O. Boehm, G. Bravos, V. Chatzigiannakis, C. Cugnasco, G. Demetriou, I. Eleftheriou, L. Fodor, S. Fotis, S. Ioannidis, D. Jakovetic, L. Kallipolitis, V. Katusic, E. Kavakli, D. Kopanaki, C. Leventis, M. Maawad Marcos, R. Martin de Pozuelo, M. Martínez, N. Milosevic, E. Pere Pages Montanera, G. Ristow, H. Ruiz-Ocampo, R. Sakellariou, R. Sirvent, S. Skrbic, I. Spais, G. Vasiliadis, M. Vinov, “Big Data Analytics in the Banking Sector: Guidelines and Lessons Learned from the CaixaBank Case,” In: Curry, E., Auer, S., Berre, A.J., Metzger, A., Perez, M.S., Zillner, S. (eds) Technologies and Applications for Big Data Value . Springer, Cham. https://doi.org/10.1007/978-3-030-78307-5_13

·        A. Alexopoulos, Y. Becerra, O. Boehm, G. Bravos, V. Chatzigiannakis, C. Cugnasco, G. Demetriou, I. Eleftheriou, S. Fotis, G. Genchi, S. Ioannidis, D. Jakovetic, L. Kallipolitis, V. Katusic, E. Kavakli, D. Kopanaki, C. Leventis, M. Martínez, J. Mascolo, N. Milosevic, E. Pere Pages Montanera, G. Ristow, H. Ruiz-Ocampo, R. Sakellariou, R. Sirvent, S. Skrbic, I. Spais, G. Danilo Spennacchio, D. Stamenkovic, G. Vasiliadis, M. Vinov, “Big Data Analytics in the Manufacturing Sector: Guidelines and Lessons Learned through the CRF Case,” In: Curry, E., Auer, S., Berre, A.J., Metzger, A., Perez, M.S., Zillner, S. (eds) Technologies and Applications for Big Data Value . Springer, Cham. https://doi.org/10.1007/978-3-030-78307-5_15

 

Journal papers and preprints

·        A. Armacki, D. Bajovic, D. Jakovetic, S. Kar, One-Shot Federated Learning for Model Clustering and Learning in Heterogeneous Environments, CoRR abs/2209.10866, 2022

·        D. Bajovic, D. Jakovetic, S. Kar, Large deviations rates for stochastic gradient descent with strongly convex functions. CoRR abs/2211.00969, 2022

·        A. Armacki, D. Bajovic, D. Jakovetic, S. Kar, Personalized Federated Learning via Convex Clustering. CoRR abs/2202.00718, 2022

·        L. Fodor, D. Jakovetic, D. Boberic Krsticev, S. Skrbic, A parallel ADMM-based convex clustering method, EURASIP J. Adv. Signal Process,  2022(1): 108, 2022

·        G. Bravos, A. J. Cabrera, C. Correa, D. Danilovic, N. Evangeliou, G. Ezov, Z. Gajica, D. Jakovetic, L. Kallipolitis, M. Lukic, J. Mascolo, D. Masera, R. Mazo, I. Mezei, A. Miaoudakis, N. Miloševic, W. Oliff, J. Robin, M. Smyrlis, G. Sakellari, G. Stamatis, D. Stamenkovic, S. Skrbic, C. Souveyet, S. Vantolas, G. Vasiliadis, D. Vukobratovic, Cybersecurity for Industrial Internet of Things: Architecture, Models and Lessons Learned, IEEE Access, 2022, doi: 10.1109/ACCESS.2022.3225074.

·        D. Jakovetic, D. Bajovic, A. K. Sahu, S. Kar, N. Milosevic, D. Stamenkovic, Nonlinear Gradient Mappings And Stochastic Optimization: A General Framework With Applications To Heavy-Tail Noise, SIAM Journal on Optimization, 2022, to appear

·        M. Savic, V. Kurbalija, M. Ilic, M. Ivanovic, D. Jakovetic, A. Valachis, S. Autexier, J. Rust, T. Kosmidis, The Application of Machine Learning Techniques in Prediction of Quality of Life Features for Cancer Patients, Computer Science and Information Systems, 2022

·        D. Jakovetić, N. Krejić, N. Krklec Jerinkić, EFIX: Exact Fixed Point Methods for Distributed Optimization, Journal of Global Optimization, 2022

·        D. Jakovetic, M. Vukovic, D. Bajovic, A. K. Sahu, S. Kar, Distributed Recursive Estimation Under Heavy-Tail Communication Noise, 2022, available at: https://github.com/dusanjakovetic/Large-scale-and-distributed-optimization-learning-and-inference/blob/main/DistributedRecursiveHeavyTail.pdf

·        D. Jakovetic, N. Krejic, N. Krklec Jerinkic, A Hessian inversion-free exact second order method for distributed consensus optimization, IEEE Transactions on Signal and Information Processing over Networks ( Volume: 8), pp. 755 – 770, 2022

·        G. Malaspina, D. Jakovetic, N. Krejic, Linear Convergence Rate Analysis of a Class of Exact First-Order Distributed Methods for Time-Varying Directed Networks and Uncoordinated Step Sizes, 2021, available at: https://arxiv.org/pdf/2007.08837.pdf

·        S. Rackovic, C. Soares, D. Jakovetic, Z. Desnica, Accurate, Interpretable, and Fast Animation: An Iterative, Sparse, and Nonconvex Approach, 2021, available at: https://arxiv.org/abs/2109.08356

·        D. Jakovetic, N. Krejic, N. Krklec Jerinkic, G. Malaspina, A. Micheletti, Distributed fixed point method for solving systems of linear algebraic equations, Automatica, vol. 134, 2021.

·        L. Fodor, D. Jakovetic, N. Krejic, N. Krklec Jerinkic, S. Skrbic, Performance evaluation and analysis of distributed multi-agent optimization algorithms with sparsified directed communication, EURASIP J. Adv. Signal Processing, 2021.

·        M. Savic, J. Atanasijevic, D. Jakovetic, N. Krejic, Tax Evasion Risk Management Using a Hybrid Unsupervised Outlier Detection Method, Expert Syst. Appl. 193: 116409, 2022

·        M. Savic, M. Lukic, D. Danilovic, Z. Bodroski, D. Bajovic, I. Mezei, D. Vukobratovic, S. Skrbic, D. Jakovetic, Deep Learning Anomaly Detection for Cellular IoT With Applications in Smart Logistics, IEEE Access, vol. 9, pp. 59406-59419, 2021.

·        D. Jakovetic, D. Bajovic, J. M. F. Xavier, J. M. F. Moura, Primal-Dual Methods for Large-Scale and Distributed Convex Optimization and Data Analytics. Proceedings of the IEEE, 108(11): 1923-1938, 2020.

·        D. Bajovic, D. Jakovetic, N. Krejic, N. Krklec Jerinkic, Distributed second order methods with Increasing number of working nodes, IEEE Transactions on Automatic Control, 2020, DOI: 10.1109/TAC.2019.2922191

·        M. Panic, D. Jakovetic, D. Vukobratovic, V. Crnojevic, A. Pizurica, MRI Reconstruction Using Markov Random Field and Total Variation as Composite Prior, Sensors 20(11), 3185, 2020.

·        D. Jakovetic, A Unification and Generalization of Exact Distributed First-Order Methods, IEEE Trans. Signal and Information Processing over Networks, vol. 5, no. 1, pp. 31-46, 2019.

·        R. Xin, D. Jakovetic, U. A. Khan, Distributed Nesterov Gradient Methods Over Arbitrary Graphs, IEEE Signal Processing Letters, vol. 26, no. 8, pp. 1247-1251, 2019.

·        D. Jakovetić, N. Krejić, N. Krklec Jerinkić, Exact spectral-like gradient method for distributed optimization, Computational Optimization and Applications, vol. 74, no. 3, pp. 703–728., 2019.

·        K. He, D. Jakovetic, B. Zhao, V. Stankovic, L. Stankovic and S. Cheng, A Generic Optimisation-based Approach for Improving Non-intrusive Load Monitoring, IEEE Transactions on Smart Grid, 2019.

·        J. Atanasijević, D. Jakovetić, N. Krejić, N. Krklec Jerinkić, D. Marković, Using Big Data Analytics to Improve Efiiciency of Tax Collection in the Tax Administration of the Republic of Serbia, Ekonomika preduzeća, pp. 115-130., 2019.

·        A.K. Sahu, D. Jakovetic, D. Bajovic, S. Kar, „Communication Efficient Distributed Weighted Non-Linear Least Squares Estimation,“ Eurasip Journal on Advances in Signal Processing, Article number: 66, 2018.

·        A.K. Sahu, D. Jakovetic, S. Kar, “CIRFE: A Distributed Random Fields Estimator”, IEEE Transactions on Signal Processing, 2018.

·        A.K. Sahu, D. Jakovetic, S. Kar, “Communication Optimality Trade-offs For Distributed Estimation”, submitted, 2018.

·        B. Sikoparija, O. Marko, M. Panic, D Jakovetic, P Radisic, „How to prepare a pollen calendar for forecasting daily pollen concentrations of Ambrosia, Betula and Poaceae?“, Aerobiologia, 1-15 D, 2018.

·        D. Bajović, D. Jakovetic, N. Krejic, N. Krklec Jerinkic, „Parallel Stochastic Line Search Methods with Feedback for Minimizing Finite Sums“, submitted, 2017.

·        D. Bajovic, D. Jakovetic, N. Krejic, N. Krklec Jerinkic, „Newton-like Method with Diagonal Correction for Distributed Optimization,“ SIAM Journal on Optimization, vol. 27, no. 2, pp. 1171-1203, 2017.

·        F. K. van Evert, S. Fountas, D. Jakovetic, V. Crnojevic, I. Travlos, C. Kempenaar, „Big Data for weed control and crop protection,“ Weed Research, vol. 57, no. 4, pp. 218-233, August 2017.

·        D. Jakovetic, D. Bajovic, N. Krejic, and N. Krklec Jerinkic, “Distributed Gradient Methods with Variable Number of Working Nodes,” IEEE Trans. Signal Processing, vol. 64, no. 15, pp. 4080-4095, 2016.

·        D. Vukobratovic, D. Jakovetic, V. Skachek, D. Bajovic, D. Sejdinovic, G. Karabulut-Kurt, C. Hollanti, and I. Fischer, “CONDENSE: A Reconfigurable Knowledge Acquisition Architecture for Future 5G IoT,” IEEE Access 4, pp. 3360-3378, 2016.

·        D. Jakovetic, J. M. F. Moura, and J. Xavier, “Linear Convergence Rate of a Class of Distributed Augmented Lagrangian Algorithms ,” IEEE Transactions on Automatic Control, vol. 60, no. 4, pp. 922 - 936, April 2015.

·        D. Jakovetic, D. Bajovic, D. Vukobratovic, and V. Crnojevic, “Cooperative Slotted Aloha for Multi-Base Station Systems,” IEEE Transactions on Communications, vol. 63, no. 4, pp. 1443 - 1456, April 2015.

·        D. Jakovetic, J. Xavier and J. M. F. Moura, “Convergence Rates of Distributed Nesterov-like Gradient Methods on Random Networks,” IEEE Transactions on Signal Processing, vol. 62, no. 4, pp. 868 - 882, February 2014.

·        D. Jakovetic, J. Xavier, and J. M. F. Moura, “Fast distributed gradient methods,” IEEE Transactions on Automatic Control, vol. 59, no. 5, pp. 1131 - 1146, May 2014.

·        D. Bajovic, D. Jakovetic, J. M. F. Moura, J. Xavier, and B. Sinopoli, “Large Deviations Performance of Consensus+Innovations Distributed Detection with non-Gaussian Observations,” IEEE Transactions on Signal Processing, vol. 60, no. 11, pp. 5987-6002, November 2012.

·        D. Jakovetic, J. M. F. Moura, and J. Xavier, “Distributed Detection over Noisy Networks: Large Deviations Analysis,” IEEE Transactions on Signal Processing, vol. 60, no. 8, pp. 4306-4320, August 2012.

·        D. Bajovic, D. Jakovetic, J. Xavier, B. Sinopoli and J. M. F. Moura, “Distributed detection via Gaussian running consensus: large deviations asymptotic analysis,” IEEE Transactions on Signal Processing, vol. 59, no. 9, pp. 4381-4396, September 2011.

·        D. Jakovetic, J. Xavier and J. M. F. Moura, “Cooperative convex optimization in networked systems: augmented Lagrangian algorithms with directed gossip communication,” IEEE Transactions on Signal Processing, vol. 59, no. 8, pp. 3889-3902, August 2011.

·        D. Jakovetic, J. Xavier and J. M. F. Moura, “Weight optimization for consensus algorithms with correlated switching topology,” IEEE Transactions on Signal Processing, vol. 58, no. 7, pp. 3788-3801, July 2010.

Conference papers (accepted/published)

 

• A. Armacki, D. Bajovic, D. Jakovetic, S. Kar, Gradient Based Clustering. International Conference on Machine Learning, ICML 2022, pp. 929-947, 2022
• N. Milosevic, D. Jakovetic, S. Skrbic, M. Savic, D. Stamenkovic, J. Mascolo, D. Masera, BACS: A comprehensive tool for deep learning-based anomaly detection in edge-fog-cloud systems,  European Signal Processing Conference, EUSIPCO 2022, pp. 1097-1101, 2022
• D. Vukobratovic, M. Lukic, I. Mezei, D. Bajovic, D. Danilovic, M. Savic, Z. Bodroski, S. Skrbic, D. Jakovetic, Edge Machine Learning in 3GPP NB-IoT: Architecture, Applications and Demonstration, European Signal Processing Conference, EUSIPCO 2022, pp.707-711, 2022

·        A. Armacki, D. Bajovic, D. Jakovetic, S. Kar, Personalized Federated Learning via Convex Clustering, IEEE International Smart Cities Conference, ISC2, 2022

• S.Rackovic, C. Soares, D. Jakovetic, Z. Desnica, R. Ljubobratovic, Clustering of the Blendshape Facial Model, 29th European Signal Processing Conference, EUSIPCO, pp. 1556-1560, 2021.
• M. Savic, V. Kurbalija, M. Ilic, M. Ivanovic, D. Jakovetic, A. Valachis, S. Autexier, J. Rust, T. Kosmidis, Analysis of Machine Learning Models Predicting Quality of Life for Cancer Patients. 12th International ACM Conference on Management of Digital EcoSystems, MEDES 2021, pp. 35-42, 2021.
• I.Arapakis, Y. Becerra, O. Boehm, G. Bravos, V. Chatzigiannakis, C. Cugnasco, G. Demetriou, I. Eleftheriou, J. Mascolo, L. Fodor, S. Ioannidis, D. Jakovetic, L. Kallipolitis, E. Kavakli, D. Kopanaki, N. Kourtellis, M. Marcos, R. Martín de Pozuelo, N. Milosevic, G. Morandi, E. Pages, G. H. Ristow, R. Sakellariou, R. Sirvent, S. Skrbic, I. Spais, G. Vasiliadis, M. Vinov, Towards Specification of a Software Architecture for Cross-Sectoral Big Data Applications, IEEE SERVICES 2019, pp. 394-395
• A. Armacki, D. Jakovetić, N. Krejić, N. Krklec Jerinkić, Distributed Trust-Region Method with the First Order Models, IEEE EUROCON 2019 -18th International Conference on Smart Technologies, 2019.
• D. Jakovetić, N. Krejić, N. Krklec Jerinkić, Spectral-like gradient method for distributed optimization, IEEE EUROCON 2019 -18th International Conference on Smart Technologies, 2019.
• A.Kumar Sahu, D. Jakovetic, D. Bajovic, S. Kar, Communication efficient distributed estimation over directed networks, IEEE EUROCON 2019 -18th International Conference on Smart Technologies, 2019.
• A. Kumar Sahu, D. Jakovetic, D. Bajovic, S. Kar, Convergence rates for distributed stochastic optimization over random networks, IEEE International Conference on Decision and Control, CDC 2018, Dec 17-19, Miami, FL, USA, invited
• A. Kumar Sahu, D. Jakovetic, D. Bajovic, S. Kar Non-asymptotic rates for communication efficient distributed zeroth order strongly convex optimization, GlobalSIP 2018, IEEE Global conference on signal and information processing, Nov 26- 28, Anaheim, CA, USA
• A. Kumar Sahu, D. Jakovetic, D. Bajovic, S. Kar, Distributed Zeroth Order Optimization Over Random Networks: A Kiefer-Wolfowitz Stochastic Approximation Approach, IEEE International Conference on Decision and Control, CDC 2018, Dec 17-19, Miami, FL, USA
• A. Kumar Sahu, D. Jakovetic, D. Bajovic, S. Kar, CREDO: A Communication-Efficient Distributed Estimation Algorithm. IEEE International Symposium on Information Theory,  ISIT 2018, pp. 516-520
• D. Bajovic, D. Jakovetic, A. Sahu, S. Kar, Large Deviations for Products of Non-I.i.d. Stochastic Matrices with Application to Distributed Detection, IEEE International Symposium on Information Theory,  ISIT 2018, pp. 1061-1065
• M. Panic, D. Jakovetic, V. Crnojevic, and A. Pizurica, Image inpainting and demosaicing via total variation and Markov random field-based modeling, TELFOR 2018, 26th Telecommunications forum, Belgrade, Serbia, 2018.
• K. Anoh, D. Bajovic, D. Vukobratovic, B. Adebisi, D. Jakovetic, and M. Cosovic, Distributed Energy Trading with Communication Constraints, ISGT Conference, 2018.

·        K. He, D. Jakovetic, V. Stankovic, and L. Stankovic, “Post-processing for event-based non-intrusive load monitoring,” NILM2018 4th International Workshop on Non-intrusive Load Monitoring, Austin, March 2018.

·        A.  Mastilovic, D. Vukobratovic, D. Jakovetic, D. Bajovic, „Cooperative Slotted ALOHA for massive M2M random access using directional antennas“, ICC 2017, IEEE International Conference on Communications, ICC Workshops, pp. 731-736, Paris, France, May 2017

·        D. Vukobratovic, D. Jakovetic, V. Skachek, D. Bajovic, D. Sejdinovic, „Network function computation as a service in future 5G machine type communications,“ ISTC 2016, 9th International Symposium on Turbo Codes and Iterative Information Processing, pp. 365-369, Brest, France, Sep. 2016.

·        D. Jakovetic, D. Bajovic, N. Krejic, N. Krklec Jerinkic, „Distributed first and second order methods with increasing number of working nodes,“ GlobalSIP 2016,  IEEE Global Conference on Signal and Information Processing, pp. 480-484, Washington, DC, USA, Dec. 2016, invited

·        D. Jakovetic, D. Bajovic, and D. Vukobratovic: "Distributed Estimation of Sparse User Activity for Multi-Base Station On-Off Random Access," to appear in proc. IEEE International Conference on Communications 2015 - MASSAP Workshop, London, UK, June 2015.

·        D. Jakovetic, A. Minja, D. Bajovic, and D. Vukobratovic: "Distributed Storage Allocations for Neighbourhood-Based Data Access," to appear in proc. IEEE Information Theory Workshop 2015, Jerusalem, Israel, April 2015.

·        D. Bajovic, D. Jakovetic, D. Vukobratovic, and V. Crnojevic: "Slotted ALOHA for Networked Base Stations: Algorithms and Performance," European Wireless 2014, pp. 1-6, Barcelona, Spain, May 2014.

·        D. Jakovetic, D. Bajovic, D. Vukobratovic, and V. Crnojevic: "Slotted ALOHA for Networked Base Stations with Spatial and Temporal Diversity," IEEE International Symposium on Information Theory, pp. 1578 - 1582, ISIT 2014, Honolulu, Hawaii, July 2014.

·        D. Bajovic, D. Jakovetic, D. Vukobratovic, and V. Crnojevic: "Slotted ALOHA for Networked Base Stations," IEEE International Conference on Communications ICC 2014 - MASSAP Workshop, pp. 520 - 526, Sydney, Australia, June 2014.

·        D. Jakovetic, J. Xavier, and J. M. F. Moura, “Distributed Nesterov Gradient Methods for Random Networks: Convergence in Probability and Convergence Rates,” IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP'14, pp. 1508 – 1511,  Florence, Italy, May 2014, invited

·        D. Jakovetic, J. M. F. Moura, and J. Xavier, “Distributed Augmented Lagrangian Algorithms: Convergence Rate,” 1st IEEE Global Conference on Signal and Information Processing, pp. 563-566, Austin, Texas, USA, December 2013, invited

·        D. Jakovetic, J. M. F. Moura, and J. Xavier, “Distributed Nesterov-like Gradient Algorithms,” CDC 2012, 51st IEEE Conference on Decision and Control, pp. 5459-5464, Maui, Hawaii, December 2012, invited

·        D. Jakovetic, J. Xavier, J. M. F. Moura, “Convergence Rate Analysis of Distributed Gradient Methods for Smooth Optimization,” 20th Telecommunications Forum, pp. 867-870, Belgrade, Serbia, November 2012

·        D. Jakovetic, J. M. F. Moura, and J. Xavier, “Consensus+Innovations Detection: Phase Transition Under Communication Noise,” 50th Annual Allerton Conference on Communication, Control, and Computing, pp. 1559-1563, Monticello, Illinois, October 2012, invited

·        D. Jakovetic, J. M. F. Moura, and J. Xavier, “Fast Cooperative Distributed Learning,” 46th Asilomar Conference on Signals, Systems and Computers, pp. 1513-1517, Pacific Grove, California, November 2012, invited

·        D. Bajovic, D. Jakovetic, J. Xavier, B. Sinopoli and J. M. F. Moura, “Asymptotic Performance of Distributed Detection over Random Networks,” IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP'11, pp. 3008–3011, Prague, Czech Republic, May 2011

·        D. Bajovic, D. Jakovetic, J. M. F. Moura, J. Xavier and B. Sinopoli, “Large Deviations Analysis of Consensus+innovations Detection in Random Networks,” 49th Allerton Conference on Communication, Control, and Computing, pp. 5987-6002, Illinois, USA, September 2011, invited

·        D. Bajovic, D. Jakovetic, J. Xavier, B. Sinopoli and J. M. F. Moura, “Distributed Detection over Time Varying Networks: Large Deviations Analysis,” 48th Allerton Conference on Communication, Control, and Computing, pp. 302 – 309, Illinois, USA, October 2010.

·        D. Jakovetic, J. Xavier and J. M. F. Moura, “Consensus in Correlated Random Topologies: Weights for Finite Time Horizon,” IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP'10, pp. 2974-2977, Dallas, Texas, USA, March 2010.