Publications
Books, Monographs, and Book Chapters
A. Nedić Distributed Optimization over Networks, a contributed chapter in the book Multi-agent Optimization, Lecture Notes in Mathematics, Springer Verlag, CIME Foundation Subseries, F. Facchinei and J.-S. Pang (Eds.), 2018 (Cetraro Italy 2014).
A. Nedić, A. Olshevsky, and W. Shi Decentralized Consensus Optimization and Resource Allocation, Lecture Notes in Mathematics, Springer Verlag, Vol. 2227, pp. 247–287, 2018 (contributions of 2017 LCCC Workshop).
A. Nedić, A. Olshevsky and M.G. Rabbat Network Topology and Communication – Computation Tradeoffs in Decentralized Optimization, Proceedings of the IEEE, Volume 106, No. 5, pp. 953–976, 2018.
A. Nedić and J. Liu Distributed Optimization for Control, Annual Review of Control, Robotics, and Autonomous Systems, Volume I, pp. 77-103, 2018.
S. Bolouki, A. Nedić and T. Basar Social Networks, a chapter in Handbook on Dynamic Game Theory edited by T. Basar and G. Zaccour, Springer International Publishing, 2017.
I. Necoara, A. Patrascu and A. Nedić Computational complexity certifications for inexact dual first order methods and its application to real-time MPC a book chapter in the edited book Developments in Model-Based Optimization and Control, edited by S. Olaru, A. Grancharova, and F.L. Pereira, Series in Lecture Notes in Control and Information Sciences, Springer International Publishing, Switzerland, pp. 2–26, 2015.
A. Nedić Convergence Rate of Distributed Averaging Dynamics and Optimization in Networks Foundations and Trends in Systems and Control, volume 2, no. 1, pp 1-100, 2015.
K. Srivastava, A. Nedić and D. Stipanovic Distributed Bregman-Distance Algorithms for Min-Max Optimization a chapter in the book Agent-Based Optimization I. Czarnowski, P. Jedrzejowicz and J. Kacprzyk (Eds.), Springer Studies in Computational Intelligence (SCI), pp. 143-174, 2013.
S.S. Ram, V.V. Veeravalli and A. Nedić Distributed and Recursive Parameter Estimation in the book Sensor Networks: Where Theory Meets Practice G. Ferrari (Ed.), Springer-Verlag, pp. 17-38, 2009.
A. Nedić and A. Ozdaglar Cooperative Distributed Multi-Agent Optimization in the book Convex Optimization in Signal Processing and Communications Y. Eldar and D. Palomar (Eds.), Cambridge University Press, pp. 340-386, 2010.
D.P. Bertsekas, V. Borkar and A. Nedić Improved Temporal Difference Methods with Linear Function Approximation MIT LIDS Report LIDS-P-2573, Dec. 2003, published in Learning and Approximate Dynamic Programming, by Barto A., Powell W., and Si J., (Eds.), IEEE Press, 2004.
D.P. Bertsekas, A. Nedić and A.E. Ozdaglar Convex Analysis and Optimization Athena Scientific, Belmont, MA, 2003.
Tutorial and Expository Articles
A. Nedić, A. Olshevsky, and C.A. Uribe A Tutorial on Distributed (Non-Bayesian) Learning: Problem, Algorithms and Results in Proceedings of the 55th IEEE Conference on Decision and Control, Las Vegas, December 14–17, 2016.
A. Nedić Distributed Optimization expository article for Encyclopedia of Systems and Control, Eds. T. Samad and J. Baillieul, Springer-Verlag, London 2014.
A. Nedić Lagrangian Optimization Methods for Nonlinear Programming Wiley Encyclopedia of Operations Research and Management Science, Eds. J.J. Cochran, L. A. Cox, P. Keskinocak, J.P. Kharoufeh, and J.C. Smith, John Wiley & Sons. Inc., February 2011.
Journal Papers
W. Ananduta, A. Nedić, and C. Ocampo-Martinez Distributed Augmented Lagrangian Method for Link-Based Resource Sharing Problems of Multi-Agent Systems submitted September 2019.
G. Belgioioso, A. Nedić, and S. Grammatico Distributed generalized Nash equilibrium seeking in aggregative games on time-varying networks, accepted in IEEE Transactions on Automatic Control, June 2020
P.E. Paré, J. Liu, C.L. Beck, A. Nedić, and T. Başar Analysis and Control of Multi-Competitive Viruses with Mutations over Time-Varying Networks, accepted in Automatica, August 2020.
A. Jalilzadeh, A. Nedić, U.V. Shanbhag, F. Yousefian A Variable Sample-size Stochastic Quasi-Newton Method for Smooth and Nonsmooth Stochastic Convex Optimization accepted in Mathematics of Operations Research, November 2020.
C.A. Uribe, S. Lee, A. Gasnikov, and A. Nedić Optimal Algorithms For Distributed Optimization to appear in Optimization Methods and Software, accepted March 2020.
T. Tatarenko, W. Shi and A. Nedić Geometric Convergence of Gradient Play Algorithms for Distributed Nash Equilibrium Seeking to appear in IEEE Transactions on Automatic Control 2021, accepted December 2020.
T. Tatarenko and A. Nedić A Smooth Inexact Penalty Reformulation of Convex Problems with Linear Constraints submitted August 2018
S. Pu and A. Nedić Distributed Stochastic Gradient Tracking Methods accepted in Mathematical Programming, March 2020.
S. Pu, W. Shi, J. Xu, A. Nedić Push-Pull Gradient Methods for Distributed Optimization in Networks IEEE Transactions on Automatioc Control 66 (1) 1-16, 2021.
N. Karakoc, A. Scaglione, A. Nedić, and M. Reisslein Multi-layer Decomposition of Network Utility Maximization Problems IEEE/ACM Transactionson Networking 28 (5) 2077-2091, 2020.
H-T. Wai, W. Shi, C.A. Uribe, A. Nedić, and A. Scaglione Accelerating Incremental Gradient Optimization with Curvature Information Computational Optimization and Applications 76 (2) 347–380, 2020.
R. Xi, S. Pu, A. Nedić, and U.A. Khan A general framework for decentralized optimization with first-order methods Proceedings of the IEEE 108 (11) 1869–1889, 2020.
A. Nedić Distributed gradient methods for convex machine learning problems in networks IEEE Signal Processing Magazine 37 (3) 92–101, 2020.
F. Yousefian, A. Nedić, and U.V. Shanbhag On stochastic and deterministic quasi-Newton methods for nonstrongly convex optimization: asymptotic convergence and rate analysis SIAM Journal on Optimization 30 (2) 1144–1172, 2020
A. Rogozin, C. Uribe, A. Gasnikov, N. Malkovskii, and A. Nedić Optimal distributed convex optimization on slowly time-varying graphs IEEE Transactions on Control of Network Systems 7 (2) 829-841, 2020
A. Nedić and I. Necoara Random minibatch projection algorithms for convex problems with functional constraints Applied Mathematics and Optimization Journal, 80 (3) 801-833, 2019, preliminary version on arxiv.
J. Liu, P.E. Paré, A. Nedić, C.Y. Tang, C.L. Beck, and T. Başar Analysis and Control of a Continuous-Time Bi-Virus Model IEEE Transactions on Automatic Control, 64 (12) 4891-4906, 2019, a preliminary version on ARXIV.
A. Nedić, A. Olshevsky, and C.A. Uribe Graph-Theoretic Analysis of Belief Systems Dynamics under Logic Constraints Scientific Reports, 9 (1), page 8843, 2019.
S. Bhatti, C. Beck, and A. Nedić Data Clustering and Graph Partitioning via Simulated Mixing IEEE Transactions on Control of Network Systems 6 (3) 253-266, 2019.
C. Wilson, V.V Veeravalli, and A. Nedić Adaptive Sequential Stochastic Optimization IEEE Transactions on Automatic Control 64 (2) 496-509, 2019.
S.R. Etesami, S. Bolouki, A. Nedić, T. Başar, and H.V. Poor Influence of Conformist and Manipulative Behaviors on Public Opinion IEEE Transactions on Control of Network Systems 6 (1) 202-214, 2019.
F. Yousefian, A. Nedić, and U.V. Shanbhag On stochastic mirror-prox algorithms for stochastic Cartesian variational inequalities: randomized block coordinate and optimal averaging schemes Set-valued and Variational Analysis 26 (4) 789-819, 2018.
P.E. Paré, C.L. Beck, and A. Nedić Epidemic Processes over Time-Varying Networks IEEE Transactions on Control of Network Systems 5 (3) 1322-1334, 2018.
S. Lee, A. Nedić, and M. Raginsky Coordinate Dual Averaging for Decentralized Online Optimization with Nonseparable Global Objectives IEEE Transactions on Control of Network Systems 5 (1) 34-44, 2018.
A. Nedić, A. Olshevsky, and W. Shi Achieving Linear Convergence For Distributed Optimization Over Time-Varying Graphs SIAM Journal on Optimization 27 (4) 2597-2633, 2017.
S. Lee, A. Nedić, and M. Raginsky Stochastic Dual-averaging for Decentralized Online Optimization on Time-varying Communication Graphs IEEE Transactions on Automatic Control 62 (12) 6407-6414, 2017.
K. Cohen, A. Nedić, and R. Srikant On Projected Stochastic Gradient Descent Algorithm with Weighted Averaging for Least Squares Regression IEEE Transactions on Automatic Control 62 (11) 5974-5981, 2017.
A. Nedić, A. Olshevsky, and C.A. Uribe Non-asymptotic Convergence Rates for Distributed Non-Bayesian Learning IEEE Transactions on Automatic Control 62 (11) 5538-5553, 2017.
F. Yousefian, A. Nedić, and U.V. Shanbhag On Smoothing, Regularization and Averaging in Stochastic Approximation Methods for Stochastic Variational Inequalities Mathematical Programing, Series B 165 (1) 391-431, 2017.
J. Liu, A.S. Morse, A. Nedić, and T. Basar Exponential Convergence of a Distributed Algorithm for Solving Linear Algebraic Equations Automatica (83) 37-46, 2017 report on ARXIV
M.T. Hale, A. Nedić, and M. Egerstedt Asynchronous Multi-Agent Primal-Dual Optimization IEEE Transactions on Automatic Control 62 (9) 4421-4435, 2017.
K. Cohen, A. Nedić, and R. Srikant Distributed Learning Algorithms for Spectrum Sharing in Spatial Random Access Wireless Networks IEEE Transactions on Automatic Control 62 (6) 2854-2869, 2017.
A. Nedić and J. Liu On Convergence Rate of Weighted-Averaging Dynamics for Consensus Problems IEEE Transactions on Automatic Control 62 (2) 766–781, 2017.
A. Nedić and A. Olshevsky Stochastic Gradient-push for Strongly Convex Functions on Time-varying Directed Graphs IEEE Transactions on Automatic Control 61 (12) 3936–3947, 2016.
J. Koshal, A. Nedić, and U. V. Shanbhag Distributed Algorithms for Aggregative Games on Graphs Operatoins Research 64 (3) 680–704, 2016
M. Raginsky and A. Nedić Online Discrete Optimization in Social Networks in the Presence of Knightian Uncertainty Operations Research 64 (3) 662–679, 2016
F. Yousefian, A. Nedić, and U. V. Shanbhag Self-Tuned Stochastic Approximation Schemes for Non-Lipschitzian Stochastic Multi-User Optimization and Nash Games, IEEE Transactions on Automatic Control 61 (7) 1753–1766, 2016
S. Lee and A. Nedić Asynchronous Gossip-Based Random Projection Algorithms Over Networks IEEE Transactions on Automatic Control 61 (4) 953-968, 2016, report on ARXIV
A. Nedić and A. Olshevsky Distributed Optimization over Time-varying Directed Graphs IEEE Transactions on Automatic Control 60 (3) 601-615, 2015, extended report on ARXIV
T-H. Chang, A. Nedić, and A. Scaglione Distributed Constrained Optimization by Consensus-Based Primal-Dual Perturbation Method IEEE Transactions on Automatic Control 59 (6) 1524-1538, 2014
A. Beck, A. Nedić, A. Ozdaglar, and M. Teboulle Optimal Distributed Gradient Methods for Network Resource Allocation Problems the inaugural issue of the IEEE Transactions on Control of Network Systems 1 (1) 64-74, 2014.
A. Nedić and S. Lee On Stochastic Subgradient Mirror-Descent Algorithm with Weighted Averaging SIAM Journal on Optimization 24 (1) 84-107, 2014, extended report on ARXIV
B. Touri and A. Nedić Product of Random Stochastic Matrices IEEE Transactions on Automatic Control 59 (2) 437-448, 2014.
S. Lee and A. Nedić Distributed Random Projection Algorithm for Convex Optimization IEEE Journal of Selected Topics in Signal Processing, a special issue on Adaptation and Learning over Complex Networks, 7, 221-229, 2013.
V. Skachek, O. Milenkovic, and A. Nedić Hybrid Noncoherent Network Coding IEEE Transactions on Information Theory 59 (6) 3317-3331, 2013. Preliminary version HERE
A. Nedić and D. Bauso Dynamic Coalitional TU Games: Distributed Bargaining among Players’ Neighbors IEEE Transactions on Automatic Control 58 (6) 1363-1376, 2013. Preliminary version HERE
J. Koshal, A. Nedić and U.V. Shanbhag Regularized Iterative Stochastic Approximation Methods for Variational Inequality Problems IEEE Transactions on Automatic Control, 58 (3), 594-609, 2013. Preliminary version HERE
B. Touri and A. Nedić On Backward Product of Stochastic Matrices Automatica 48 (8) 1477-1488, 2012. Preliminary version HERE
B. Touri and A. Nedić On Approximations and Ergodicity Classes in Random Chains IEEE Transactions on Automatic Control 57 (11) 2718-2730, 2012.
F. Yousefian, A. Nedić and U.V. Shanbhag On stochastic gradient and subgradient methods with adaptive steplength sequences a shorter version appeared in Automatica 48 (1) 56-67, 2012.
S.S. Ram, A. Nedić and V.V. Veeravalli A New Class of Distributed Optimization Algorithms: Application to Regression of Distributed Data Optimization Methods and Software 27(1) 71–88, 2012. Preliminary version HERE
B. Touri and A. Nedić On Ergodicity, Infinite Flow and Consensus in Random Models IEEE Transactions on Automatic Control 56 (7) 1593-1605, 2011. Preliminary version HERE
J. Koshal, A. Nedić and U.V. Shanbhag Multiuser Optimization: Distributed Algorithms and Error Analysis SIAM Journal on Optimization 21(3) 1046-1081, 2011. Preliminary version HERE
K. Srivastava and A. Nedić Distributed Asynchronous Constrained Stochastic Optimization IEEE Journal of Selected Topics in Signal Processing 5 (4) 772-790, 2011. Preliminary version HERE.
A. Nedić Random Algorithms for Convex Minimization Problems Mathematical Programming, Series B, Special issue in honor of Paul Tseng, 129, 225-253, 2011. Preliminary version HERE
A. Nedić Asynchronous Broadcast-Based Convex Optimization over a Network IEEE Transactions on Automatic Control 56 (6) 1337-1351, 2011. Preliminary version HERE Special thanks to Jayash Koshal for his generous help with simulations.
S.S. Ram, A. Nedić and V.V. Veeravalli Distributed Stochastic Subgradient Projection Algorithms for Convex Optimization Journal of Optimization Theory and Applications 147 (3) 516-545, 2010. Preliminary version HERE
S.S. Ram, A. Nedić and V.V. Veeravalli Incremental Stochastic Subgradient Algorithms for Convex Optimization SIAM Journal on Optimization 20 (2) 691-717, 2009. Preliminary version HERE
S.S. Ram, V.V. Veeravalli and A. Nedić Distributed and Recursive Parameter Estimation in Parametrized Linear State-Space Models IEEE Transactions on Automatic Control 55 (2) 488-492, 2010. Preliminary version HERE
A. Nedić, A. Ozdaglar, and A.P. Parrilo Constrained Consensus and Optimization in Multi-Agent Networks IEEE Transactions on Automatic Control 55 (4) 922–938, 2010. Preliminary version HERE
A. Nedić, A. Olshevsky, A. Ozdaglar and J.N. Tsitsiklis On Distributed Averaging Algorithms and Quantization Effects IEEE Transactions on Automatic Control 54 (11) 2506–2517, 2009. Preliminary version HERE A short paper appeared in Proc. of the 47th CDC Conference, 4825-4830, 2008.
A. Nedić and A. Ozdaglar Convergence Rate for Consensus with Delays Journal of Global Optimization 47 (3) 437–456, 2010. Preliminary version HERE
A. Nedić and D.P. Bertsekas The Effect of Deterministic Noise in Subgradient Methods Mathematical Programming 125 (1) 75-99, 2010. Preliminary version HERE
A. Nedić and A. Ozdaglar Subgradient Methods for Saddle-Point Problems Journal of Optimization Theory and Applications 142 (1) 205-228, 2009. Preliminary version HERE
A. Nedić and A. Ozdaglar Distributed Subgradient Methods for Multi-agent Optimization IEEE Transactions on Automatic Control 54 (1) 48-61, 2009. Preliminary version HERE
A. Nedić and A. Ozdaglar Approximate Primal Solutions and Rate Analysis for Dual Subgradient Methods SIAM Journal on Optimization 19 (4) 1757-1780, 2009. Preliminary version HERE
A. Nedić and A. Ozdaglar Separation of Nonconvex Sets with General Augmenting Functions Mathematics of Operations Research 33 (3) 587–605, 2008. Preliminary version HERE
A. Nedić and A. Ozdaglar A Geometric Framework for Nonconvex Optimization Duality using Augmented Lagrangian Functions Journal of Global Optimization 40 (4) 545–573, 2008. Preliminary version HERE
A. Nedić, A. Ozdaglar and A. Rubinov Abstract Convexity for Non-convex Optimization Duality Optimization, vol. 56, 655–674, 2007. Preliminary version HERE
A. Nedić and D.P. Bertsekas Least-Squares Policy Evaluation Algorithms with Linear Function Approximation MIT LIDS Report LIDS-P-2537, Dec. 2001, published in Journal of Discrete Event Systems, Vol. 13, pp. 79-110, 2003.
A. Nedić Subgradient Methods for Convex Minimization MIT Thesis, May 2002.
D.P. Bertsekas, A. Nedić and A.E. Ozdaglar Min Common/Max Crossing Duality: A Simple Geometric Framework for Convex Optimization and Minimax Theory MIT LIDS Report LIDS-P-2536, Jan. 2002.
A. Nedić and D.P. Bertsekas Incremental Subgradient Methods for Nondifferentiable Optimization MIT LIDS Report LIDS-P-2460, Dec. 2000, SIAM J. on Optimization, Vol. 12, pp. 109-138, 2001.
A. Nedić, D.P. Bertsekas and V. Borkar Distributed Asynchronous Incremental Subgradient Methods Proceedings of the March 2000 Haifa Workshop “Inherently Parallel Algorithms in Feasibility and Optimization and Their Applications”, D. Butnariu, Y. Censor, and S. Reich, Eds., Elsevier, Amsterdam, 2001.
A. Nedić and D.P. Bertsekas Convergence Rate of Incremental Subgradient Algorithms Stochastic Optimization: Algorithms and Applications, S. Uryasev and P. M. Pardalos, (Eds.), Kluwer Academic Publishers, pp. 263-304, 2000.
Conference Papers
A. Nedić and T. Tatarenko Convergence Rate of a Penalty Method for Strongly Convex Problems with Linear Constraints Proceedings of the 59th IEEE Conference on Decision and Control (CDC), Jeju Island, Republic of Korea, Dec. 14-18, 2020, pp. 372-377.
W. Ananduta, C. Ocampo-Martinez, and A. Nedić Accelerated Multi-Agent Optimization Method over Stochastic Networks Proceedings of the 59th IEEE Conference on Decision and Control (CDC), Jeju Island, Republic of Korea, Dec. 14-18, 2020, pp. 2961-2966.
T. Tatarenko and A. Nedić On geometric convergence of distributed gradient play Online-proceedings of the IFAC World Congress (IFAC), Berlin, Germany, July 11-17, 2020, pp. 3429-3434.
P. Thaker, G. Dasarathy, and A. Nedić On the Sample Complexity and Optimization Landscape for Quadratic Feasibility Problems IEEE International Symposium on Information Theory (ISIT), Los Angeles, CA, June 21-26, 2020, pp. 1438-1443.
G. Belgioioso, A. Nedić, and S. Grammatico Distributed generalized Nash equilibrium seeking in aggregative games Proceedings of the 58th IEEE Conference on Decision and Control (CDC 2019), Nice, France Dec. 11-13, 2019, pp. 5948-5954.
A. Nedić and I. Necoara Random minibatch projection algorithms for convex feasibility problems Proceedings of the 58th IEEE Conference on Decision and Control (CDC 2019), Nice, France Dec. 11-13, 2019, pp. 1507-1512.
N. Ravi, A. Scaglione, and A. Nedić A Case of Distributed Optimization in an Adversarial Environment IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2019), Brighton, United Kingdom, May 12-17, 2019, pp. 5252-5256.
C.A. Uribe, D. Dvinskikh, P. Dvurechensky, A. Gasnikov and A. Nedić Distributed Computation of Wasserstein Barycenters over Networks Proceedings of the 57th IEEE Conference on Decision and Control (CDC 2018), Miami Beach, FL, Dec. 17-19, 2018, pp. 8544-8549.
A. Jalilzadeh, A. Nedić, U.V. Shanbhag, and F.Yousefian A Variable Sample-size Stochastic Quasi-Newton Method for Smooth and Nonsmooth Stochastic Convex Optimization Proceedings of the 57th IEEE Conference on Decision and Control (CDC 2018), Miami Beach, FL, USA, Dec. 17-19, 2018, pp. 4097-4102.
T. Tatarenko, W. Shi and A. Nedić Accelerated Gradient Play Algorithm for Distributed Nash Equilibrium Seeking Proceedings of the 57th IEEE Conference on Decision and Control (CDC 2018), Miami Beach, FL, Dec. 17-19, 2018, pp. 3561-3566.
S. Pu, W. Shi, J. Xi and A. Nedić A Push-Pull Gradient Method for Distributed Optimization in Networks Proceedings of the 57th IEEE Conference on Decision and Control (CDC 2018), Miami Beach, FL, Dec. 17-19, 2018, pp. 3385-3390.
H-T. Wai, N. Freris, A. Nedić and A. Scaglione SUCAG: Stochastic Unbiased Curvature-aided Gradient Method for Distributed Optimization Proceedings of the 57th IEEE Conference on Decision and Control (CDC 2018), Miami Beach, FL, Dec. 17-19, 2018, pp. 1751-1756.
J. Liu, M. Ye, B.D.O. Anderson, T. Basar and A. Nedić Discrete-Time Polar Opinion Dynamics with Heterogeneous Individuals Proceedings of the 57th IEEE Conference on Decision and Control (CDC 2018), Miami Beach, FL, Dec. 17-19, 2018, pp. 1694-1699.
S. Pu and A. Nedić A Distributed Stochastic Gradient Tracking Method Proceedings of the 57th IEEE Conference on Decision and Control (CDC 2018), Miami Beach, FL, Dec. 17-19, 2018, pp. 963-968.
N. Karakoc, A. Scaglione and A. Nedić Multi-layer Decomposition of Optimal Resource Sharing Problems Proceedings of the 57th IEEE Conference on Decision and Control (CDC 2018), Miami Beach, FL, Dec. 17-19, 2018, pp. 178-183.
A. Nedić, A.Olshevsky and W. Shi Improved Convergence Rates for Distributed Resource Allocation Proceedings of the 57th IEEE Conference on Decision and Control (CDC 2018), Miami Beach, FL, Dec. 17-19, 2018, pp. 172-177.
P. Dvurechensky, D. Dvinskikh, A. Gasnikov, C.A. Uribe and A. Nedić Decentralize and Randomize: Faster Algorithm for Wasserstein Barycenters NIPS (Spotlight presentation), Montreal, Canada, Dec. 2-8, 2018, preliminary version on arxiv at https://arxiv.org/pdf/1806.03915.pdf.
S.X. Wu, H.-T. Wai, A. Scaglione, A. Nedić, and A. Leshem Data injection attack on decentralized optimization, Proceedings of 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2018), Calgary, Alberta, Canada, April 15-20, 2018, pp. 3644-3648.
A. Nedić and T. Tatarenko On Stochastic Proximal-Point Method for Convex-Composite Optimization, Proceedings of the 55th Allerton Conference on Communication, Control and Computing, Monticello, Illinois, October 3–6, 2017, pp. 198–203.
H-T. Wai, W. Shi, A. Nedić and A. Scaglione Curvature-aided Incremental Aggregated Gradient Method, Proceedings of the 55th Allerton Conference on Communication, Control and Computing, Monticello, Illinois, October 3–6, 2017, pp. 526–532.
S. Bolouki, D.G. Dobakhshari, T. Basar, V. Gupta and A. Nedić Applications of Group Testing to Security Decision-Making in NetworksProceedings of the 56th IEEE Conference on Decision and Control (CDC 2017), Melbourne, Australia, December 12–14, 2017, pp. 2929–2934.
J. Liu, Y. Liu, A. Nedić and T. Basar An Approach to Distributed Parametric Learning with Streaming Data Proceedings of the 56th IEEE Conference on Decision and Control (CDC 2017), Melbourne, Australia, December 12–14, 2017, pp. 3206–3211.
J. Liu, P.E. Pare, A. Nedić, C.L. Beck, and T. Basar On a Continuous-Time Multi-Group Bi-Virus Model with Human Awareness Proceedings of the 56th IEEE Conference on Decision and Control (CDC 2017), Melbourne, Australia, December 12–14, 2017, pp. 4124–4129.
F. Yousefian, A. Nedić and U.V. Shanbhag A Smoothing Stochastic Quasi-Newton Method for Non-Lipschitzian Stochastic Optimization Problems Proceedings of the 2017 Winter Simulation Conference, Las Vegas, NV, Dec. 3–6, 2017, pp. 2291–2302.
S.R. Etesami, S. Bolouki, T. Basar and A. Nedić Evolution of Public Opinion under Conformist and Manipulative Behaviors Proceedings of the 20th IFAC World Congress (IFAC WC 2017) Toulouse, France, July 9–14, 2017, pp. 14909–14914.
S.Bolouki, M.H.Manshaei, V.Ravanmehr, A. Nedić and T. Basar Group Testing Game Proceedings of the 20th IFAC World Congress (IFAC WC 2017) Toulouse, France, July 9–14, 2017, pp. 10078–10083.
A. Nedić, A. Olshevsky, W. Shi, and C.A. Uribe Geometrically Convergent Distributed Optimization with Uncoordinated Step-Sizes Proceedings of the IEEE American Control Conference (ACC) 2017, Seattle, WA, May 24–26, 2017, pp. 3950–3955.
P.E. Pare, J. Liu, C.L. Beck, A. Nedić, and T. Basar Multi-Competitive Viruses over Static and Time-Varying Networks Proceedings of the IEEE American Control Conference (ACC) 2017, Seattle, WA, May 24–26, 2017, pp. 1685–1690.
J. Liu, D. Fullmer, A. Nedić, and T. Basar A Distributed Algorithm for Computing a Common Fixed Point of a Family of Strongly Quasi-nonexpansive Maps Proceedings of the IEEE American Control Conference (ACC) 2017, Seattle, WA, May 24–26, 2017, pp. 686–690.
A. Nedić, A. Olshevsky, and C.A. Uribe Distributed Gaussian Learning over Time-Varying Directed Graphs Proceedings of the 50th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, Nov.6–9, 2016, pp. 1710–1714.
S.R. Etesami, S. Bolouki, A. Nedić and T. Basar Conformity versus Manipulation in Reputation Systems Proceedings of the 55th Decision and Control Conference (CDC 2016), Las Vegas, NV, December 12–14, 2016, pp. 4451–4456.
J. Liu, T. Basar, and A. Nedić Input-Output Stability of Linear Consensus Proceedings of the 55th Decision and Control Conference (CDC 2016), Las Vegas, NV, December 12–14, 2016, pp. 6978–6983.
A. Nedić, A. Olshevsky and W. Shi A Geometrically Convergent Method for Distributed Optimization over Time-Varying Directed Graphs Proceedings of the 55th Decision and Control Conference (CDC 2016), Las Vegas, NV, December 12–14, 2016, pp. 1023–1029.
A. Nedić, A. Olshevsky and C. A. Uribe Distributed Learning with Infinitely Many Hypotheses Proceedings of the 55th Decision and Control Conference (CDC 2016), Las Vegas, NV, December 12–14, 2016, pp. 6321–6326.
F. Yousefian, A. Nedić, and U. V. Shanbhag Stochastic Quasi-Newton Methods for Non-strongly Convex Problems: Convergence and Rate Analysis Proceedings of the 55th Decision and Control Conference (CDC 2016), Las Vegas, NV, December 12–14, 2016, pp. 4496–4503.
J. Liu, P. E. Pare, A. Nedić, C-Y. Tang, C.L. Beck, and T. Basar On the Analysis of a Continuous-Time Bi-Virus Model Proceedings of the 55th Decision and Control Conference (CDC 2016), Las Vegas, NV, December 12–14, 2016, pp. 290–295.
S. Bhatti, C. Beck and A. Nedić Large Scale Data Clustering and Graph Partitioning via Simulated Mixing Proceedings of the 55th Decision and Control Conference (CDC 2016), Las Vegas, NV, December 12–14, 2016, pp. 147-152.
A. Nedić, A. Olshevsky and W. Shi Linearly Convergent Decentralized Consensus Optimization over Directed Networks 2016 IEEE Gliobal Conference on Signal and Information Processing (GlobalSIP), Washington DC, December 7-9, 2016, pp. 485-489.
A. Nedić, A. Olshevsky and C.A. Uribe Network Independent Rates in Distributed Learning Proceedings of the 2016 American Control Conference (ACC), Boston, MA, July 6–8, 2016, pp. 1072–1077.
R.S. Etesami, A. Nedić and T. Basar Generalization of An Accelerated Successive Projection Method for Convex Feasibility Problems Proceedings of the 2016 American Control Conference (ACC), Boston, MA, July 6–8, 2016, pp. 4422–4427.
A. Nedić, S. Lee and M. Raginsky Decentralized Online Optimization With Global Objectives and Local Communication Proceedings of the 2016 American Control Conference (ACC), Boston, MA, July 6–8, 2016, pp. 4497–4503.
S. Bolouki, A. Nedić and T. Basar On the Steady-State Range of Averaging Dynamics Proceedings of the 2016 American Control Conference (ACC), Boston, MA, July 6–8, 2016, pp. 6447–6452.
J. Liu, X. Chen, T. Basar and A. Nedić A Continuous-Time Distributed Algorithm for Solving Linear Equations Proceedings of the 2016 American Control Conference, Boston, MA, July 6–8, 2016, pp. 5551–5556.
K. Cohen, A. Nedić and R. Srikant On Projected Stochastic Gradient Descent Algorithm with Weighted Averaging for Least Squares Regression Proceedings of the 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016) Shanghai, China, March 20–25, 2016
A. Kannan, A. Nedić and U.V. Shanbhag Distributed Stochastic Optimization under Imperfect Information Proceedings of the 54th Conference on Decision and Control (CDC), Osaka, Japan, December 15–18, 2015, pp. 400–405; extended version on ARXIV.
M. T. Hale, A. Nedić and M. Egerstedt Hybrid Centralized/Decentralized Multi-Agent Optimization with Communication Delays Proceedings of the 54th Conference on Decision and Control (CDC), Osaka, Japan, December 15–18, 2015, pp. 700–705.
P. E. Pare, C. L. Beck and A. Nedić Stability Analysis and Control of Virus Spread over Time-Varying Networks Proceedings of the 54th Conference on Decision and Control (CDC), Osaka, Japan, December 15–18, 2015, pp. 3554–3559.
I. Necoara and A. Nedić A fully distributed dual gradient method with linear convergence for large-scale separable convex problems Proceedings of the 14th European Control Conference (ECC) 2015, Johannes Kepler University, Linz, Austria, July 15-17, 2015, pp. 305-309.
A. Nedić, A. Olshevsky and C.A. Uribe Nonasymptotic Convergence Rates for Cooperative Learning Over Time-Varying Directed Graphs American Control Conference (ACC), Chicago, IL, July 1-3, 2015, pp. 5884-5889.
A. Nedić, S. Lee and M. Raginsky Decentralized Online Optimization with Global Objectives and Local Communication American Control Conference (ACC), Chicago, IL, July 1-3, 2015, pp. 4497-4503.
K. Cohen, A. Nedić and R. Srikant Distributed Learning Algorithms for Spectrum Sharing in Spatial Random Access Networks Proceedings of the 13th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt 2015), The Best Paper Award, IIT Bombay, 25-29 May 2015, pp. 513-520.
C. Wilson, V. V. Veeravalli and A. Nedić Dynamic Stochastic Optimization Proceedings of the 53 IEEE Conference on Decision and Control (CDC) 2014, Los Angeles, California, December 15–17, 2014, pp. 173-178.
C. Singh, A. Nedić and R. Srikant Random Block Coordinate Gradient Projection Algorithms Proceedings of the 53rd IEEE Conference on Decision and Control, Los Angeles, California, December 15-17, 2014, pp. 185-190.
J. Liu, A.S. Morse, A. Nedić and T. Basar Internal Stability of Linear Consensus Processes Proceedings of the 53rd IEEE Conference on Decision and Control, Los Angeles, California, December 15-17, 2014, pp. 922-927.
J. Liu, A. Nedić and T. Basar Complex Constrained Consensus Proceedings of the 53 IEEE Conference on Decision and Control (CDC) 2014, Los Angeles, California, December 15–17, 2014, pp. 1464-1469.
J. Liu, A.S. Morse, A. Nedić and T. Basar Stability of a Distributed Algorithm for Solving Linear Algebraic Equations Proceedings of the 53 IEEE Conference on Decision and Control (CDC) 2014, Los Angeles, California, December 15–17, 2014, pp. 3707-3712.
F. Yousefian, A. Nedić, and U. V. Shanbhag Optimal robust smoothing extragradient algorithms for stochastic variational inequality problems Proceedings of the 53 IEEE Conference on Decision and Control (CDC) 2014, Los Angeles, California, December 15–17, 2014, pp. 5831-5836.
A. Nedić and J. Liu A Lyapunov Approach to Discrete-Time Linear Consensus Proceedings of the 2nd Global Conference on Signal and Information Processing (GlobalSIP) 2014, Atlanta, Georgia, December 3-5, 2014, pp. 842-846.
M. Raginsky and A. Nedić Online Discrete Optimization in Social Networks Proceedings of IEEE American Control Conference (ACC), Portland, Oregon, June 4-6, 2014, pp. 3796-3801.
C. Singh, A. Nedić and R. Srikant LP-relaxation based Distributed Algorithms for Scheduling in Wireless Networks Proceedings of IEEE INFOCOM, Toronto, Canada, April 27 – May 2, 2014, pp. 1905-1913.
A. Nedic and A. Olshevsky Distributed optimization over time-varying directed graphs Proceedings of the 52nd IEEE Conference on Decision and Control, Florence, Italy, December 10-13, 2013, pp. 6855-6860.
S. Lee and A. Nedić Gossip-based Random Projection Algorithm for Distributed Optimization: Error Bounds Proceedings of the 52nd IEEE Conference on Decision and Control, Florence, Italy, December 10-13, 2013, pp. 6874-6879.
F. Yousefian, A. Nedić and U. V. Shanbhag A Regularized Smoothing Stochastic Approximation (RSSA) Algorithm for Stochastic Variational Inequality Problems Proceedings of the 2013 Winter Simulation Conference, R. Pasupathy, S.-H. Kim, A. Tolk, R. Hill, and M. E. Kuhl, eds., Washington, DC, December 8-11, 2013, pp. 933-944. The Best Theoretical Paper Award of the 2013 Winter Simulation Conference.
A. Nedić and A. Olshevsky Distributed Optimization of Strongly Convex Functions on Directed Time-Varying Graphs Proceedings of the inaugural IEEE Global Conference on Signal and Information Processing (GlobalSIP 2013) Conference, Austin, Texas, December 3-5, 2013, pp. 329-332.
S. Lee and A. Nedić Distributed Mini-batch Random Projection Algorithms for Reduced Communication Overhead Proceedings of the inaugural IEEE Global Conference on Signal and Information Processing (GlobalSIP) Conference, Austin, Texas, December 3-5, 2013, pp. 559-562.
T-H. Chang, A. Nedić and A. Scaglione Distributed sparse regression by consensus-based primal-dual perturbation optimization Proceedings of the inaugural IEEE Global Conference on Signal and Information Processing (GlobalSIP 2013) Conference, Austin, Texas, December 3-5, 2013, pp. 289-292.
B. Touri, F. Farnoud, A. Nedić and O. Milenkovic A General Framework for Distributed Vote Aggregation, IEEE American Control Conference (ACC), Washington, DC, USA, June 17-19, 2013, pp. 3833-3838.
S.R. Etesami, T. Basar, A. Nedić and B. Touri Termination Time of Multidimensional Hegselmann-Krause Opinion Dynamics IEEE American Control Conference (ACC), Washington, DC, USA, June 17-19, 2013, pp. 1257-1262.
F. Yousefian, A. Nedić and U.V. Shanbhag A distributed adaptive steplength stochastic approximation method for monotone stochastic Nash Games IEEE American Control Conference (ACC), Washington, DC, USA, June 17-19, 2013, pp. 4772-4777.
S. Lee and A. Nedić Epoch Gradient Descent for Smoothed Hinge-loss Linear SVMs IEEE American Control Conference (ACC), Washington, DC, USA, June 17-19, 2013, pp. 4796-4801.
S. Lee and A. Nedić DrSVM: Distributed Random Projection Algorithms for SVMs Proceedings of the 51st IEEE Conference on Decision and Control (CDC), Maui, Hawaii, December 9-13, 2012, pp. 5286-5291.
A. Nedić and B. Touri Multi-Dimensional Hegselmann-Krause Dynamics Proceedings of the 51st IEEE Conference on Decision and Control (CDC), Maui, Hawaii, December 9-13, 2012, pp. 68-73.
B. Touri, T. Basar and A. Nedić On Averaging Dynamics in General State Spaces Proceedings of the 51st IEEE Conference on Decision and Control (CDC), Maui, Hawaii, December 9-13, 2012, pp. 62-67.
J. Koshal, A. Nedić and U.V. Shanbhag A Gossip Algorithm for Aggregative Games on Graphs Proceedings of the 51st IEEE Conference on Decision and Control (CDC), Maui, Hawaii, December 9-13, 2012, pp. 4840-4845.
M. Rabbat and A. Nedić Convergence Properties of Normalized Random Incremental Gradient Algorithms for Least-squares Source Localization Proceedings of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), November, 4-7, 2012, Pacific Grove, CA, pp. 1417-1421.
S. Lee and A. Nedić Asynchronous Gossip-Based Random Projection Algorithms for Fully Distributed Problems Proceedings of 2012 Asilomar Conference on Signals, Systems, and Computers, November 4-7, 2012, Pacific Grove, CA.
V. Skachek, O. Milenkovic and A. Nedić Hybrid Noncoherent Network Coding Proceedings of the 2012 International Symposium on Network Coding (NETCOD), Boston, June 29-30, 2012.
A. Nedić and D. Bauso Constrained Consensus for Bargaining in Dynamic Coalitional TU Games Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC), Orlando, Florida, December 2011, pp. 229-234.
B. Touri and A. Nedić Alternative Characterization of Ergodicity for Doubly Stochastic Chains Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC), Orlando, Florida, December 2011, pp. 5371-5376.
B. Touri and A. Nedić On Existence of a Quadratic Comparison Function for Random Weighted Averaging Dynamics and Its Implications Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC), Orlando, Florida, December 2011, pp. 3806-3811.
B. Touri and A. Nedić Discrete Time Opinion Dynamics Proceedings of the Asilomar Conference on Signals, Systems, and Computers, Asilomar, November 6-9, 2011, Pacific Grove, California, pages 1172-1176.
F. Yousefian, A. Nedić and U.V. Shanbhag A regularized adaptive steplength stochastic approximation scheme for monotone stochastic variational inequalities to appear in Proceedings of the 2011 Winter Simulation Conference, S. Jain, R. R. Creasey, J. Himmelspach, K. P. White, and M. Fu, eds., 2011, pp. 4110-4121.
J. Koshal, A. Nedić, and U.V. Shanbhag Single Timescale Stochastic Approximation for Stochastic Nash Games in Cognitive Radio Systems Proceedings of the 17th Digital Signal Processing Conference (DSP), July 2011
K. Srivastava, A. Nedić and D. Stipanovic Distributed Min-Max Optimization in Networks Proceedings of the 17th Digital Signal Processing Conference (DSP), July 2011
B. Touri and A. Nedić Approximation and Limiting Behavior of Random Models the 49th IEEE Conference on Decision and Control, Atlanta, Georgia, December 2010, pp. 2656-2663.
B. Touri and A. Nedić When Infinite Flow is Sufficient for Ergodicity the 49th IEEE Conference on Decision and Control, Atlanta, Georgia, December 2010, pp. 7479-7486.
J. Koshal, A. Nedić and U.V. Shanbhag Single Timescale Regularized Stochastic Approximation Schemes for Monotone Nash Games under Uncertainty the 49th IEEE Conference on Decision and Control, Atlanta, Georgia, December 2010, pp. 231-236.
K. Srivastava, A. Nedić and D. Stipanovic Distributed Constrained Optimization over Noisy Networks the 49th IEEE Conference on Decision and Control, Atlanta, Georgia, December 2010, pp. 1945-1950
A. Nedić Random Projection Algorithms for Convex Set Intersection Problems the 49th IEEE Conference on Decision and Control, Atlanta, Georgia, December 2010, pp. 7655-7660
S.S. Ram, A. Nedić and V.V. Veeravalli Asynchronous Gossip Algorithms for Stochastic Optimization: Constant Stepsize Analysis in edited book on Recent Advances in Optimization and its Applications in Engineering volume of the 14th Belgian-French-German Conference on Optimization (BFG), M. Diehl, F. Glineur, E. Jarlebring and W. Michiels (Eds.), 2010, pp. 51-60.
F. Yousefian, A. Nedić and U.V. Shanbhag Convex Nondifferentaible Stochastic Optimization: A Local Randomized Smoothing Technique IEEE American Control Conference, Baltimore, USA 2010, pp. 4875-4880.
B. Touri, A. Nedić and S.S. Ram Asynchronous stochastic convex optimization over random networks: Error bounds Proceedings of the Information Theory and Applications Workshop (ITA), San Diego 2010
S.S. Ram, A. Nedić and V.V. Veeravalli Asynchronous Gossip Algorithms for Stochastic Optimization Proceedings of the 48th IEEE Conference on Decision and Control, Shanghai, China, December 2009, pp. 3581-3586.
J. Koshal, A. Nedić and U.V. Shanbhag Distributed Multi-User Optimization: Algorithms and Error Analysis Proceedings of the 48th IEEE Conference on Decision and Control, Shanghai, China, December 2009, pp. 4372-4377.
B. Touri and A. Nedić Distributed Consensus over Network with Noisy Links 12th International Conference on Information Fusion, July 2009, pp. 146-154.
A. Nedić and V.G. Subramanian Approximately Optimal Utility Maximization IEEE Information Workshop on Networking and Information Theory, ITW 2009, Volos, Greece, pp. 206-210.
S.S. Ram, A. Nedić and V.V. Veeravalli Distributed Subgradient Projection Algorithm for Convex Optimization IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Taipei, Taiwan, April 2009, pp. 3653-3656.
S.S. Ram, V.V. Veeravalli, and A. Nedić Distributed Non-Autonomous Power Control through Distributed Convex Optimization The 28th IEEE Conference on Computer Communications INFOCOM, Rio de Janeiro, Brazil, pp. 3001-3005, 19-25 April 2009.
D. Acemoglu, A. Nedić and A. Ozdaglar Convergence of Rule-of-Thumb Learning Rules in Social Networks Proceedings of the 47th IEEE Conference on Decision and Control, Cancun, Mexico, 2008, pp. 1714-1720.
A. Nedić, A. Olshevsky, A. Ozdaglar and J.N. Tsitsiklis Distributed Subgradient Methods and Quantization Effects Proceedings of the 47th IEEE Conference on Decision and Control, Cancun, Mexico, 2008, pp. 4177-4184.
P.A. Bliman, A. Nedić and A. Ozdaglar Rate of Convergence for Consensus with Delays Proceedings of the 47th IEEE Conference on Decision and Control, Cancun, Mexico, 2008, pp. 4849-4854.
S.S. Ram, V.V. Veeravalli and A. Nedić Incremental recursive prediction error algorithm for parameter estimation in sensor networks The 11th International Conference on Information Fusion, June 30-July 3, 2008, pp. 1-8.
A. Nedić and A. Ozdaglar Subgradient Methods in Network Resource Allocation: Rate Analysis 42nd Annual Conference on Information Sciences and Systems, CISS 2008, Princeton, March 2008, pp. 1189-1194.
A. Nedić and A. Ozdaglar On the Rate of Convergence of Distributed Asynchronous Subgradient Methods for Multi-agent Optimization Proceedings of the 46th IEEE Conference on Decision and Control, New Orleans, USA, 2007, pp. 4711-4716.
S.S. Ram, V.V. Veeravalli and A. Nedić Incremental Robbins-Monro Gradient Algorithm for Regression in Sensor Networks The 2-nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMPSAP 12-14 Dec. 2007, pp. 309-312.
