Alex Olshevsky

ORCID

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 81

Top Venues

CoRR

IEEE Trans. Autom. Control.

CDC

ACC

Publications

Haoxing Tian, Ioannis Ch. Paschalidis, Alex Olshevsky
One-Shot Averaging for Distributed TD (λ) Under Markov Sampling. IEEE Control. Syst. Lett. 8 (2024)
Arsenii Mustafin, Aleksei Pakharev, Alex Olshevsky, Ioannis Ch. Paschalidis
MDP Geometry, Normalization and Value Free Solvers. CoRR (2024)
Haoxing Tian, Ioannis Ch. Paschalidis, Alex Olshevsky
One-Shot Averaging for Distributed TD(λ) Under Markov Sampling. CoRR (2024)
Julien M. Hendrickx, Alex Olshevsky
Convex SGD: Generalization Without Early Stopping. CoRR (2024)
Mahtab Talaei, Apostolos I. Rikos, Alex Olshevsky, Laura F. White, Ioannis Ch. Paschalidis
Network-Based Epidemic Control Through Optimal Travel and Quarantine Management. CoRR (2024)
Qianqian Ma, Yang-Yu Liu, Alex Olshevsky
Optimal Fixed Lockdown for Pandemic Control. IEEE Trans. Autom. Control. 69 (7) (2024)
Amirreza Neshaei Moghaddam, Alex Olshevsky, Bahman Gharesifard
Sample Complexity of the Linear Quadratic Regulator: A Reinforcement Learning Lens. CoRR (2024)
Ryan Yu, Alex Olshevsky, Peter Chin
Tree Search for Simultaneous Move Games via Equilibrium Approximation. CoRR (2024)
Arsenii Mustafin, Alex Olshevsky, Ioannis Ch. Paschalidis
On Value Iteration Convergence in Connected MDPs. CoRR (2024)
Rui Liu, Alex Olshevsky
Distributed TD(0) With Almost No Communication. IEEE Control. Syst. Lett. 7 (2023)
Alex Olshevsky, Bahman Gharesifard
A Small Gain Analysis of Single Timescale Actor Critic. SIAM J. Control. Optim. 61 (2) (2023)
Haoxing Tian, Alex Olshevsky, Yannis Paschalidis
Convergence of Actor-Critic with Multi-Layer Neural Networks. NeurIPS (2023)
Haoxing Tian, Ioannis Ch. Paschalidis, Alex Olshevsky
On the Performance of Temporal Difference Learning With Neural Networks. CoRR (2023)
Rui Liu, Alex Olshevsky
Distributed TD(0) with Almost No Communication. CoRR (2023)
Haoxing Tian, Ioannis Ch. Paschalidis, Alex Olshevsky
On the Performance of Temporal Difference Learning With Neural Networks. ICLR (2023)
César A. Uribe, Alex Olshevsky, Angelia Nedic
Nonasymptotic Concentration Rates in Cooperative Learning-Part I: Variational Non-Bayesian Social Learning. IEEE Trans. Control. Netw. Syst. 9 (3) (2022)
Alex Olshevsky, Bahman Gharesifard
A Small Gain Analysis of Single Timescale Actor Critic. CoRR (2022)
Arsenii Mustafin, Alex Olshevsky, Ioannis Ch. Paschalidis
Closing the gap between SVRG and TD-SVRG with Gradient Splitting. CoRR (2022)
Shi Pu, Alex Olshevsky, Ioannis Ch. Paschalidis
A Sharp Estimate on the Transient Time of Distributed Stochastic Gradient Descent. IEEE Trans. Autom. Control. 67 (11) (2022)
César A. Uribe, Alex Olshevsky, Angelia Nedic
Nonasymptotic Concentration Rates in Cooperative Learning - Part II: Inference on Compact Hypothesis Sets. IEEE Trans. Control. Netw. Syst. 9 (3) (2022)
Alex Olshevsky
Asymptotic Network Independence and Step-Size for a Distributed Subgradient Method. J. Mach. Learn. Res. 23 (2022)
Artin Spiridonoff, Alex Olshevsky, Yannis Paschalidis
Communication-efficient SGD: From Local SGD to One-Shot Averaging. NeurIPS (2021)
Rui Liu, Alex Olshevsky
Distributed TD(0) with Almost No Communication. CoRR (2021)
Rui Liu, Alex Olshevsky
Temporal Difference Learning as Gradient Splitting. ICML (2021)
Rui Liu, Alex Olshevsky
Asymptotic Convergence Rate of Alternating Minimization for Rank One Matrix Completion. IEEE Control. Syst. Lett. 5 (4) (2021)
Artin Spiridonoff, Alex Olshevsky, Ioannis Ch. Paschalidis
Communication-efficient SGD: From Local SGD to One-Shot Averaging. CoRR (2021)
Rui Liu, Alex Olshevsky
Asymptotic Convergence Rate of Alternating Minimization for Rank One Matrix Completion. CoRR (2020)
Alex Olshevsky
Asymptotic Network Independence and Step-Size for A Distributed Subgradient Method. CoRR (2020)
Qianqian Ma, Alex Olshevsky
Adversarial Crowdsourcing Through Robust Rank-One Matrix Completion. CoRR (2020)
Shi Pu, Alex Olshevsky, Ioannis Ch. Paschalidis
Asymptotic Network Independence in Distributed Stochastic Optimization for Machine Learning: Examining Distributed and Centralized Stochastic Gradient Descent. IEEE Signal Process. Mag. 37 (3) (2020)
Artin Spiridonoff, Alex Olshevsky, Ioannis Ch. Paschalidis
Robust Asynchronous Stochastic Gradient-Push: Asymptotically Optimal and Network-Independent Performance for Strongly Convex Functions. J. Mach. Learn. Res. 21 (2020)
Yao Ma, Alex Olshevsky, Csaba Szepesvári, Venkatesh Saligrama
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers. J. Mach. Learn. Res. 21 (2020)
Alex Olshevsky
On a Relaxation of Time-Varying Actuator Placement. IEEE Control. Syst. Lett. 4 (3) (2020)
Rui Liu, Alex Olshevsky
Temporal Difference Learning as Gradient Splitting. CoRR (2020)
Qianqian Ma, Alex Olshevsky
Adversarial Crowdsourcing Through Robust Rank-One Matrix Completion. NeurIPS (2020)
Artin Spiridonoff, Alex Olshevsky, Ioannis Ch. Paschalidis
Local SGD With a Communication Overhead Depending Only on the Number of Workers. CoRR (2020)
Julien M. Hendrickx, Alex Olshevsky, Venkatesh Saligrama
Minimax Rate for Learning From Pairwise Comparisons in the BTL Model. ICML (2020)
Alex Olshevsky
On the Inapproximability of the Discrete Witsenhausen Problem. IEEE Control. Syst. Lett. 3 (3) (2019)
Julien M. Hendrickx, Alex Olshevsky, Venkatesh Saligrama
Graph Resistance and Learning from Pairwise Comparisons. CoRR (2019)
Olivier Bronchain, Julien M. Hendrickx, Clément Massart, Alex Olshevsky, François-Xavier Standaert
Leakage Certification Revisited: Bounding Model Errors in Side-Channel Security Evaluations. CRYPTO (1) (2019)
Yao Ma, Alex Olshevsky, Venkatesh Saligrama, Csaba Szepesvári
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers. CoRR (2019)
Alex Olshevsky
On A Relaxation of Time-Varying Actuator Placement. CoRR (2019)
Alex Olshevsky, Ioannis Ch. Paschalidis, Shi Pu
A Non-Asymptotic Analysis of Network Independence for Distributed Stochastic Gradient Descent. CoRR (2019)
Alex Olshevsky
On the Inapproximability of the Discrete Witsenhausen Problem. CoRR (2019)
Alex Olshevsky, Ioannis Ch. Paschalidis, Shi Pu
Asymptotic Network Independence in Distributed Optimization for Machine Learning. CoRR (2019)
Ali Jadbabaie, Alex Olshevsky
Scaling Laws for Consensus Protocols Subject to Noise. IEEE Trans. Autom. Control. 64 (4) (2019)
Olivier Bronchain, Julien M. Hendrickx, Clément Massart, Alex Olshevsky, François-Xavier Standaert
Leakage Certification Revisited: Bounding Model Errors in Side-Channel Security Evaluations. IACR Cryptol. ePrint Arch. 2019 (2019)
Angelia Nedic, Alex Olshevsky, Wei Shi
Improved Convergence Rates for Distributed Resource Allocation. CDC (2018)
Theodora S. Brisimi, Ruidi Chen, Theofanie Mela, Alex Olshevsky, Ioannis Ch. Paschalidis, Wei Shi
Federated learning of predictive models from federated Electronic Health Records. Int. J. Medical Informatics 112 (2018)
Alex Olshevsky, Ioannis Ch. Paschalidis, Artin Spiridonoff
Fully Asynchronous Push-Sum With Growing Intercommunication Intervals. ACC (2018)
Ali Jadbabaie, Alex Olshevsky, Milad Siami
Limitations and Tradeoffs in Minimum Input Selection Problems. ACC (2018)
Angelia Nedic, Alex Olshevsky, César A. Uribe
Graph-Theoretic Analysis of Belief System Dynamics under Logic Constraints. CoRR (2018)
Angelia Nedic, Alex Olshevsky, Michael G. Rabbat
Network Topology and Communication-Computation Tradeoffs in Decentralized Optimization. Proc. IEEE 106 (5) (2018)
Alex Olshevsky
On (Non)Supermodularity of Average Control Energy. IEEE Trans. Control. Netw. Syst. 5 (3) (2018)
Ali Jadbabaie, Alex Olshevsky, Milad Siami
Deterministic and Randomized Actuator Scheduling With Guaranteed Performance Bounds. CoRR (2018)
Angelia Nedic, Alex Olshevsky, Wei Shi
Improved Convergence Rates for Distributed Resource Allocation. CoRR (2017)
Alex Olshevsky
Linear Time Average Consensus and Distributed Optimization on Fixed Graphs. SIAM J. Control. Optim. 55 (6) (2017)
Yao Ma, Alex Olshevsky, Venkatesh Saligrama, Csaba Szepesvári
Crowdsourcing with Sparsely Interacting Workers. CoRR (2017)
Angelia Nedic, Alex Olshevsky, César A. Uribe
Distributed Learning for Cooperative Inference. CoRR (2017)
Angelia Nedic, Alex Olshevsky, Michael G. Rabbat
Network Topology and Communication-Computation Tradeoffs in Decentralized Optimization. CoRR (2017)
Angelia Nedic, Alex Olshevsky, Wei Shi
Achieving Geometric Convergence for Distributed Optimization Over Time-Varying Graphs. SIAM J. Optim. 27 (4) (2017)
Angelia Nedic, Alex Olshevsky, Cesar A. Uribe
Fast Convergence Rates for Distributed Non-Bayesian Learning. IEEE Trans. Autom. Control. 62 (11) (2017)
Angelia Nedic, Alex Olshevsky, Wei Shi, Cesar A. Uribe
Geometrically convergent distributed optimization with uncoordinated step-sizes. ACC (2017)
Thinh T. Doan, Alex Olshevsky
Distributed resource allocation on dynamic networks in quadratic time. Syst. Control. Lett. 99 (2017)
Angelia Nedic, Alex Olshevsky, Wei Shi
Linearly convergent decentralized consensus optimization over directed networks. GlobalSIP (2016)
Angelia Nedic, Alex Olshevsky, Cesar A. Uribe
A tutorial on distributed (non-Bayesian) learning: Problem, algorithms and results. CDC (2016)
Angelia Nedic, Alex Olshevsky, Cesar A. Uribe
Network independent rates in distributed learning. ACC (2016)
Alex Olshevsky
Fast algorithms for distributed optimization and hypothesis testing: A tutorial. CDC (2016)
Angelia Nedic, Alex Olshevsky, Cesar A. Uribe
Distributed Gaussian Learning over Time-varying Directed Graphs. CoRR (2016)
Angelia Nedic, Alex Olshevsky, Cesar A. Uribe
A Tutorial on Distributed (Non-Bayesian) Learning: Problem, Algorithms and Results. CoRR (2016)
Alex Olshevsky
Eigenvalue clustering, control energy, and logarithmic capacity. Syst. Control. Lett. 96 (2016)
Angelia Nedic, Alex Olshevsky, Cesar A. Uribe
Distributed Learning with Infinitely Many Hypotheses. CoRR (2016)
Julien M. Hendrickx, Alex Olshevsky
On Symmetric Continuum Opinion Dynamics. SIAM J. Control. Optim. 54 (5) (2016)
Ali Jadbabaie, Alex Olshevsky
On performance of consensus protocols subject to noise: Role of hitting times and network structure. CDC (2016)
Angelia Nedich, Alex Olshevsky, Wei Shi
A geometrically convergent method for distributed optimization over time-varying graphs. CDC (2016)
Angelia Nedic, Alex Olshevsky, Cesar A. Uribe
Distributed learning with infinitely many hypotheses. CDC (2016)
Angelia Nedic, Alex Olshevsky, Cesar A. Uribe
Distributed Gaussian learning over time-varying directed graphs. ACSSC (2016)
Alex Olshevsky
On (Non)Supermodularity of Average Control Energy. CoRR (2016)
Angelia Nedic, Alex Olshevsky, Wei Shi, Cesar A. Uribe
Geometrically Convergent Distributed Optimization with Uncoordinated Step-Sizes. CoRR (2016)
Tamer Basar, Seyed Rasoul Etesami, Alex Olshevsky
Convergence Time of Quantized Metropolis Consensus Over Time-Varying Networks. IEEE Trans. Autom. Control. 61 (12) (2016)
Angelia Nedic, Alex Olshevsky
Stochastic Gradient-Push for Strongly Convex Functions on Time-Varying Directed Graphs. IEEE Trans. Autom. Control. 61 (12) (2016)
Peter Davison, Naomi Ehrich Leonard, Alex Olshevsky, Michael Schwemmer
Nonuniform Line Coverage From Noisy Scalar Measurements. IEEE Trans. Autom. Control. 60 (7) (2015)
Alex Olshevsky
Eigenvalue Clustering, Control Energy, and Logarithmic Capacity. CoRR (2015)
Alex Olshevsky
Minimum input selection for structural controllability. ACC (2015)
Vincent D. Blondel, Raphaël M. Jungers, Alex Olshevsky
On primitivity of sets of matrices. Autom. 61 (2015)
Tamer Basar, Seyed Rasoul Etesami, Alex Olshevsky
Fast Convergence of Quantized Consensus Using Metropolis Chains Over Static and Dynamic Networks. CoRR (2015)
Ali Jadbabaie, Alex Olshevsky
On performance of consensus protocols subject to noise: role of hitting times and network structure. CoRR (2015)
Naomi Ehrich Leonard, Alex Olshevsky
Cooperative Learning in Multiagent Systems from Intermittent Measurements. SIAM J. Control. Optim. 53 (1) (2015)
Angelia Nedic, Alex Olshevsky
Distributed Optimization Over Time-Varying Directed Graphs. IEEE Trans. Autom. Control. 60 (3) (2015)
Angelia Nedic, Alex Olshevsky, Cesar A. Uribe
Nonasymptotic convergence rates for cooperative learning over time-varying directed graphs. ACC (2015)
Alex Olshevsky
Consensus with Ternary Messages. SIAM J. Control. Optim. 52 (2) (2014)
Vincent D. Blondel, Alex Olshevsky
How to Decide Consensus? A Combinatorial Necessary and Sufficient Condition and a Proof that Consensus is Decidable but NP-Hard. SIAM J. Control. Optim. 52 (5) (2014)
Tamer Basar, Seyed Rasoul Etesami, Alex Olshevsky
Fast convergence of quantized consensus using Metropolis chains. CDC (2014)
Alex Olshevsky
Minimal Controllability Problems. IEEE Trans. Control. Netw. Syst. 1 (3) (2014)
Angelia Nedic, Alex Olshevsky
Stochastic Gradient-Push for Strongly Convex Functions on Time-Varying Directed Graphs. CoRR (2014)
Alex Olshevsky
Average Consensus in Nearly Linear Time on Fixed Graphs and Implications for Decentralized Optimization and Multi-Agent Control. CoRR (2014)
Alex Olshevsky
Minimum Input Selection for Structural Controllability. CoRR (2014)
Alex Olshevsky
Consensus with ternary messages. CDC (2013)
Vincent D. Blondel, Raphaël M. Jungers, Alex Olshevsky
On primitivity of sets of matrices. CDC (2013)
Angelia Nedic, Alex Olshevsky
Distributed optimization over time-varying directed graphs. CDC (2013)

Alex Olshevsky.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Alex Olshevsky