Network Lifetime and Power Assignment in ad hoc Wireless Networks. - Gruia Calinescu; Sanjiv Kapoor; Alexander Olshevsky; Alexander Zelikovsky (ESA, 2003)

Primal-dual algorithms for QoS multimedia multicast. - Gruia Calinescu; Cristina G. Fernandes; Ion I. Mandoiu; Alexander Olshevsky; K. Yang; Alexander Zelikovsky (GLOBECOM, 2003)

Improved Approximation Algorithms for the Quality of Service Steiner Tree Problem. - Marek Karpinski; Ion I. Mandoiu; Alexander Olshevsky; Alexander Zelikovsky (WADS, 2003)

Convergence in Multiagent Coordination, Consensus, and Flocking. - Vincent D. Blondel; Julien M. Hendrickx; Alex Olshevsky; John N. Tsitsiklis (CDC/ECC, 2005)

Improved Approximation Algorithms for the Quality of Service Multicast Tree Problem. - Marek Karpinski; Ion I. Mandoiu; Alexander Olshevsky; Alexander Zelikovsky (Algorithmica, 2005)

Convergence Rates in Distributed Consensus and Averaging. - Alex Olshevsky; John N. Tsitsiklis (CDC, 2006)

QoS Multimedia Multicast Routing. - Ion I. Mandoiu; Alex Olshevsky; Alexander Zelikovsky (Handbook of Approximation Algorithms and Metaheuristics, 2007)

Distributed subgradient methods and quantization effects. - Angelia Nedic; Alexander Olshevsky; Asuman E. Ozdaglar; John N. Tsitsiklis (CDC, 2008)

On the Nonexistence of Quadratic Lyapunov Functions for Consensus Algorithms. - Alexander Olshevsky; John N. Tsitsiklis (IEEE Trans. Autom. Control., 2008)

Distributed anonymous function computation in information fusion and multiagent systems. - Julien M. Hendrickx; Alex Olshevsky; John N. Tsitsiklis (Allerton, 2009)

Matrix P-norms are NP-hard to approximate if p neq 1,2, infty - Julien M. Hendrickx; Alexander Olshevsky (CoRR, 2009)

On the NP-Hardness of Checking Matrix Polytope Stability and Continuous-Time Switching Stability. - Leonid Gurvits; Alexander Olshevsky (IEEE Trans. Autom. Control., 2009)

On Distributed Averaging Algorithms and Quantization Effects. - Angelia Nedic; Alexander Olshevsky; Asuman E. Ozdaglar; John N. Tsitsiklis (IEEE Trans. Autom. Control., 2009)

Matrix p-Norms Are NP-Hard to Approximate If p!=q1, 2, INFINITY. - Julien M. Hendrickx; Alexander Olshevsky (SIAM J. Matrix Anal. Appl., 2010)

Efficient information aggregation strategies for distributed control and signal processing. - Alexander Olshevsky (2010)

Convergence Speed in Distributed Consensus and Averaging. - Alexander Olshevsky; John N. Tsitsiklis (SIAM Rev., 2011)

Distributed Anonymous Discrete Function Computation. - Julien M. Hendrickx; Alexander Olshevsky; John N. Tsitsiklis (IEEE Trans. Autom. Control., 2011)

A Lower Bound for Distributed Averaging Algorithms on the Line Graph. - Alexander Olshevsky; John N. Tsitsiklis (IEEE Trans. Autom. Control., 2011)

On the cost of deciding consensus. - Vincent D. Blondel; Alex Olshevsky (CDC, 2012)

Diameter, Optimal Consensus, and Graph Eigenvalues - Julien M. Hendrickx; Raphaël M. Jungers; Alexander Olshevsky; Guillaume Vankeerberghen (CoRR, 2012)

Symmetric continuum opinion dynamics: Convergence, but sometimes only in distribution. - Julien M. Hendrickx; Alex Olshevsky (CDC, 2013)

Cooperative learning in multi-agent systems from intermittent measurements. - Naomi Ehrich Leonard; Alex Olshevsky (CDC, 2013)

Combinatorial bounds and scaling laws for noise amplification in networks. - Ali Jadbabaie; Alex Olshevsky (ECC, 2013)

Distributed optimization of strongly convex functions on directed time-varying graphs. - Angelia Nedic; Alex Olshevsky (GlobalSIP, 2013)

The Minimal Controllability Problem - Alex Olshevsky (CoRR, 2013)

NP-hardness of deciding convexity of quartic polynomials and related problems. - Amir Ali Ahmadi; Alexander Olshevsky; Pablo A. Parrilo; John N. Tsitsiklis (Math. Program., 2013)

Nonuniform Coverage Control on the Line. - Naomi Ehrich Leonard; Alex Olshevsky (IEEE Trans. Autom. Control., 2013)

Degree Fluctuations and the Convergence Time of Consensus Algorithms. - Alex Olshevsky; John N. Tsitsiklis (IEEE Trans. Autom. Control., 2013)

Fast convergence of quantized consensus using Metropolis chains. - Tamer Basar; Seyed Rasoul Etesami; Alex Olshevsky (CDC, 2014)

Graph diameter, eigenvalues, and minimum-time consensus. - Julien M. Hendrickx; Raphaël M. Jungers; Alexander Olshevsky; Guillaume Vankeerberghen (Autom., 2014)

Average Consensus in Nearly Linear Time on Fixed Graphs and Implications for Decentralized Optimization and Multi-Agent Control. - Alex Olshevsky (CoRR, 2014)

How to Decide Consensus? A Combinatorial Necessary and Sufficient Condition and a Proof that Consensus is Decidable but NP-Hard. - Vincent D. Blondel; Alex Olshevsky (SIAM J. Control. Optim., 2014)

Consensus with Ternary Messages. - Alex Olshevsky (SIAM J. Control. Optim., 2014)

Minimal Controllability Problems. - Alex Olshevsky (IEEE Trans. Control. Netw. Syst., 2014)

Nonasymptotic convergence rates for cooperative learning over time-varying directed graphs. - Angelia Nedic; Alex Olshevsky; Cesar A. Uribe (ACC, 2015)

Minimum input selection for structural controllability. - Alex Olshevsky (ACC, 2015)

On primitivity of sets of matrices. - Vincent D. Blondel; Raphaël M. Jungers; Alex Olshevsky (Autom., 2015)

Fast Convergence of Quantized Consensus Using Metropolis Chains Over Static and Dynamic Networks. - Tamer Basar; Seyed Rasoul Etesami; Alex Olshevsky (CoRR, 2015)

Cooperative Learning in Multiagent Systems from Intermittent Measurements. - Naomi Ehrich Leonard; Alex Olshevsky (SIAM J. Control. Optim., 2015)

Nonuniform Line Coverage From Noisy Scalar Measurements. - Peter Davison; Naomi Ehrich Leonard; Alex Olshevsky; Michael Schwemmer (IEEE Trans. Autom. Control., 2015)

Distributed Optimization Over Time-Varying Directed Graphs. - Angelia Nedic; Alex Olshevsky (IEEE Trans. Autom. Control., 2015)

Distributed Gaussian learning over time-varying directed graphs. - Angelia Nedic; Alex Olshevsky; Cesar A. Uribe (ACSSC, 2016)

Network independent rates in distributed learning. - Angelia Nedic; Alex Olshevsky; Cesar A. Uribe (ACC, 2016)

On performance of consensus protocols subject to noise: Role of hitting times and network structure. - Ali Jadbabaie; Alex Olshevsky (CDC, 2016)

Distributed learning with infinitely many hypotheses. - Angelia Nedic; Alex Olshevsky; Cesar A. Uribe (CDC, 2016)

A tutorial on distributed (non-Bayesian) learning: Problem, algorithms and results. - Angelia Nedic; Alex Olshevsky; Cesar A. Uribe (CDC, 2016)

A geometrically convergent method for distributed optimization over time-varying graphs. - Angelia Nedich; Alex Olshevsky; Wei Shi 010 (CDC, 2016)

Fast algorithms for distributed optimization and hypothesis testing: A tutorial. - Alex Olshevsky (CDC, 2016)

Linearly convergent decentralized consensus optimization over directed networks. - Angelia Nedic; Alex Olshevsky; Wei Shi 010 (GlobalSIP, 2016)

Eigenvalue clustering, control energy, and logarithmic capacity. - Alex Olshevsky (Syst. Control. Lett., 2016)

On Symmetric Continuum Opinion Dynamics. - Julien M. Hendrickx; Alex Olshevsky (SIAM J. Control. Optim., 2016)

Convergence Time of Quantized Metropolis Consensus Over Time-Varying Networks. - Tamer Basar; Seyed Rasoul Etesami; Alex Olshevsky (IEEE Trans. Autom. Control., 2016)

Stochastic Gradient-Push for Strongly Convex Functions on Time-Varying Directed Graphs. - Angelia Nedic; Alex Olshevsky (IEEE Trans. Autom. Control., 2016)

Geometrically convergent distributed optimization with uncoordinated step-sizes. - Angelia Nedic; Alex Olshevsky; Wei Shi 010; Cesar A. Uribe (ACC, 2017)

Crowdsourcing with Sparsely Interacting Workers. - Yao Ma; Alex Olshevsky; Venkatesh Saligrama; Csaba Szepesvári (CoRR, 2017)

Distributed Learning for Cooperative Inference. - Angelia Nedic; Alex Olshevsky; César A. Uribe (CoRR, 2017)

Distributed resource allocation on dynamic networks in quadratic time. - Thinh T. Doan 001; Alex Olshevsky (Syst. Control. Lett., 2017)

Linear Time Average Consensus and Distributed Optimization on Fixed Graphs. - Alex Olshevsky (SIAM J. Control. Optim., 2017)

Achieving Geometric Convergence for Distributed Optimization Over Time-Varying Graphs. - Angelia Nedic; Alex Olshevsky; Wei Shi 010 (SIAM J. Optim., 2017)

Fast Convergence Rates for Distributed Non-Bayesian Learning. - Angelia Nedic; Alex Olshevsky; Cesar A. Uribe (IEEE Trans. Autom. Control., 2017)

QoS Multimedia Multicast Routing. - Ion I. Mandoiu; Alex Olshevsky; Alexander Zelikovsky (Handbook of Approximation Algorithms and Metaheuristics (2), 2018)

Limitations and Tradeoffs in Minimum Input Selection Problems. - Ali Jadbabaie; Alex Olshevsky; Milad Siami (ACC, 2018)

Fully Asynchronous Push-Sum With Growing Intercommunication Intervals. - Alex Olshevsky; Ioannis Ch. Paschalidis; Artin Spiridonoff (ACC, 2018)

Improved Convergence Rates for Distributed Resource Allocation. - Angelia Nedic; Alex Olshevsky; Wei Shi 010 (CDC, 2018)

Graph-Theoretic Analysis of Belief System Dynamics under Logic Constraints. - Angelia Nedic; Alex Olshevsky; César A. Uribe (CoRR, 2018)

Federated learning of predictive models from federated Electronic Health Records. - Theodora S. Brisimi; Ruidi Chen; Theofanie Mela; Alex Olshevsky; Ioannis Ch. Paschalidis; Wei Shi 010 (Int. J. Medical Informatics, 2018)

Network Topology and Communication-Computation Tradeoffs in Decentralized Optimization. - Angelia Nedic; Alex Olshevsky; Michael G. Rabbat (Proc. IEEE, 2018)

On (Non)Supermodularity of Average Control Energy. - Alex Olshevsky (IEEE Trans. Control. Netw. Syst., 2018)

Graph Resistance and Learning from Pairwise Comparisons. - Julien M. Hendrickx; Alexander Olshevsky; Venkatesh Saligrama (ICML, 2019)

A Non-Asymptotic Analysis of Network Independence for Distributed Stochastic Gradient Descent. - Alex Olshevsky; Ioannis Ch. Paschalidis; Shi Pu 004 (CoRR, 2019)

Asymptotic Network Independence in Distributed Optimization for Machine Learning. - Alex Olshevsky; Ioannis Ch. Paschalidis; Shi Pu 004 (CoRR, 2019)

On the Inapproximability of the Discrete Witsenhausen Problem. - Alex Olshevsky (IEEE Control. Syst. Lett., 2019)

Leakage Certification Revisited: Bounding Model Errors in Side-Channel Security Evaluations. - Olivier Bronchain; Julien M. Hendrickx; Clément Massart; Alex Olshevsky; François-Xavier Standaert (IACR Cryptol. ePrint Arch., 2019)

Scaling Laws for Consensus Protocols Subject to Noise. - Ali Jadbabaie; Alex Olshevsky (IEEE Trans. Autom. Control., 2019)

Minimal Reachability is Hard To Approximate. - Ali Jadbabaie; Alexander Olshevsky; George J. Pappas; Vasileios Tzoumas (IEEE Trans. Autom. Control., 2019)

Minimax Rank-$1$ Matrix Factorization. - Venkatesh Saligrama; Alexander Olshevsky; Julien M. Hendrickx (AISTATS, 2020)

Minimax Rate for Learning From Pairwise Comparisons in the BTL Model. - Julien M. Hendrickx; Alex Olshevsky; Venkatesh Saligrama (ICML, 2020)

Adversarial Crowdsourcing Through Robust Rank-One Matrix Completion. - Qianqian Ma; Alex Olshevsky (NeurIPS, 2020)

Local SGD With a Communication Overhead Depending Only on the Number of Workers. - Artin Spiridonoff; Alex Olshevsky; Ioannis Ch. Paschalidis (CoRR, 2020)

On a Relaxation of Time-Varying Actuator Placement. - Alex Olshevsky (IEEE Control. Syst. Lett., 2020)

Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers. - Yao Ma; Alex Olshevsky; Csaba Szepesvári; Venkatesh Saligrama (J. Mach. Learn. Res., 2020)

Robust Asynchronous Stochastic Gradient-Push: Asymptotically Optimal and Network-Independent Performance for Strongly Convex Functions. - Artin Spiridonoff; Alex Olshevsky; Ioannis Ch. Paschalidis (J. Mach. Learn. Res., 2020)

Asymptotic Network Independence in Distributed Stochastic Optimization for Machine Learning: Examining Distributed and Centralized Stochastic Gradient Descent. - Shi Pu 004; Alex Olshevsky; Ioannis Ch. Paschalidis (IEEE Signal Process. Mag., 2020)

Temporal Difference Learning as Gradient Splitting. - Rui Liu 030; Alex Olshevsky (ICML, 2021)

Communication-efficient SGD: From Local SGD to One-Shot Averaging. - Artin Spiridonoff; Alex Olshevsky; Yannis Paschalidis (NeurIPS, 2021)

Asymptotic Convergence Rate of Alternating Minimization for Rank One Matrix Completion. - Rui Liu 030; Alex Olshevsky (IEEE Control. Syst. Lett., 2021)

Deterministic and Randomized Actuator Scheduling With Guaranteed Performance Bounds. - Milad Siami; Alexander Olshevsky; Ali Jadbabaie (IEEE Trans. Autom. Control., 2021)

Asymptotic Network Independence and Step-Size for a Distributed Subgradient Method. - Alex Olshevsky (J. Mach. Learn. Res., 2022)

A Sharp Estimate on the Transient Time of Distributed Stochastic Gradient Descent. - Shi Pu 004; Alex Olshevsky; Ioannis Ch. Paschalidis (IEEE Trans. Autom. Control., 2022)

Guest Editorial Special Issue on Dynamics and Behaviors in Social Networks. - Claudio Altafini; Giacomo Como; Julien M. Hendrickx; Alexander Olshevsky; Alireza Tahbaz-Salehi (IEEE Trans. Control. Netw. Syst., 2022)

Nonasymptotic Concentration Rates in Cooperative Learning-Part I: Variational Non-Bayesian Social Learning. - César A. Uribe; Alex Olshevsky; Angelia Nedic (IEEE Trans. Control. Netw. Syst., 2022)

Nonasymptotic Concentration Rates in Cooperative Learning - Part II: Inference on Compact Hypothesis Sets. - César A. Uribe; Alex Olshevsky; Angelia Nedic (IEEE Trans. Control. Netw. Syst., 2022)

On the Performance of Temporal Difference Learning With Neural Networks. - Haoxing Tian; Ioannis Ch. Paschalidis; Alex Olshevsky (ICLR, 2023)

Convergence of Actor-Critic with Multi-Layer Neural Networks. - Haoxing Tian; Alex Olshevsky; Yannis Paschalidis (NeurIPS, 2023)

Distributed TD(0) With Almost No Communication. - Rui Liu 030; Alex Olshevsky (IEEE Control. Syst. Lett., 2023)

A Small Gain Analysis of Single Timescale Actor Critic. - Alex Olshevsky; Bahman Gharesifard (SIAM J. Control. Optim., 2023)

Convex SGD: Generalization Without Early Stopping. - Julien M. Hendrickx; Alex Olshevsky (CoRR, 2024)

Sample Complexity of the Linear Quadratic Regulator: A Reinforcement Learning Lens. - Amirreza Neshaei Moghaddam; Alex Olshevsky; Bahman Gharesifard (CoRR, 2024)

On Value Iteration Convergence in Connected MDPs. - Arsenii Mustafin; Alex Olshevsky; Ioannis Ch. Paschalidis (CoRR, 2024)

Tree Search for Simultaneous Move Games via Equilibrium Approximation. - Ryan Yu; Alex Olshevsky; Peter Chin 001 (CoRR, 2024)

MDP Geometry, Normalization and Value Free Solvers. - Arsenii Mustafin; Aleksei Pakharev; Alex Olshevsky; Ioannis Ch. Paschalidis (CoRR, 2024)

Network-Based Epidemic Control Through Optimal Travel and Quarantine Management. - Mahtab Talaei; Apostolos I. Rikos; Alex Olshevsky; Laura F. White; Ioannis Ch. Paschalidis (CoRR, 2024)

One-Shot Averaging for Distributed TD (λ) Under Markov Sampling. - Haoxing Tian; Ioannis Ch. Paschalidis; Alex Olshevsky (IEEE Control. Syst. Lett., 2024)

Closing the gap between SVRG and TD-SVRG with Gradient Splitting. - Arsenii Mustafin; Alex Olshevsky; Ioannis Ch. Paschalidis (Trans. Mach. Learn. Res., 2024)

Optimal Fixed Lockdown for Pandemic Control. - Qianqian Ma; Yang-Yu Liu; Alex Olshevsky (IEEE Trans. Autom. Control., 2024)

MDP Geometry, Normalization and Reward Balancing Solvers. - Arsenii Mustafin; Aleksei Pakharev; Alex Olshevsky; Ioannis Paschalidis (AISTATS, 2025)

Analysis of Value Iteration Through Absolute Probability Sequences. - Arsenii Mustafin; Sebastien Colla; Alex Olshevsky; Ioannis Ch. Paschalidis (CoRR, 2025)

Sample Complexity of Linear Quadratic Regulator Without Initial Stability. - Amirreza Neshaei Moghaddam; Alex Olshevsky; Bahman Gharesifard (CoRR, 2025)

Geometric Re-Analysis of Classical MDP Solving Algorithms. - Arsenii Mustafin; Aleksei Pakharev; Alex Olshevsky; Ioannis Ch. Paschalidis (CoRR, 2025)