Publications

Preprints

  • A. S. Donmez, Y. Arslantas, and M. O. Sayin. Team collaboration vs competition: New fictitious play dynamics for multi-team zero-sum games, arXiv:2402.02147, 2024. [url]
  • Y. Arslantas, E. Yuceel, Y. Yalin, and M. O. Sayin. Convergence of heterogeneous learning dynamics in zero-sum stochastic games, arXiv:2311.00778, 2023. [url]
  • M. O. Sayin. Decentralized learning for stochastic games: Beyond zero sum and identical interest, arXiv:2310.07256, 2023. [url]
  • M. O. Sayin and O. Unlu. Logit-Q dynamics for efficient learning in stochastic teams, arXiv:2302.09806v2, 2023. [url]

Selected Conferences

  1. M. O. Sayin, K. Zhang, and A. Ozdaglar, “Fictitious Play in Markov Games with Single Controller,” in ACM EC, 2022. [url]
  2. A. Ozdaglar, M. O. Sayin and K. Zhang. Independent Learning in Stochastic Games. In the Proceedings of the International Congress of Mathematicians (ICM’22), vol. 7, pp. 5340-5373, 2022. [url]
  3. M. O. Sayin*, K. Zhang*, D. S. Leslie, T. Başar, and A. Ozdaglar, “Decentralized Q-learning in Zero-sum Markov Games,” in NeurIPS, 2021. [url] [poster]
  4. M. O. Sayin*, K. Zhang*, D. S. Leslie, T. Başar, and A. Ozdaglar, “Decentralized Q-learning in Zero-sum Markov Games,” in Workshop on Reinforcement Learning Theory at ICML, 2021.

Journals

  1. M. O. Sayin, F. Parise, and A. Ozdaglar, “Fictitious Play in Zero-sum Stochastic Games,” SIAM J. Cont. Opt., 2022. [url][poster]
  2. M. O. Sayin and T. Başar, “Bayesian Persuasion with State-Dependent Quadratic Cost Measures,” IEEE Trans. Automatic Control, 2021. [url]
  3. M. O. Sayin and T. Başar, “Persuasion-based Robust Sensor Design Against Attackers with Unknown Control Objectives,” IEEE Trans. Automatic Control, 2021. [url]
  4. M. O. Sayin, et al., “Reliable Smart Road Signs,” IEEE Trans. Intell. Transp. Syst., 2020. [url]
  5. M. O. Sayin, E. Akyol, and T. Başar, “Hierarchical Multi-stage Gaussian Signaling Games in Noncooperative Communication and Control Systems,” Automatica, 2019. [url]
  6. M. O. Sayin, et al., “Information-driven Autonomous Intersection Control via Incentive Compatible Mechanisms,” IEEE Trans. Intell. Transp. Syst., 2019. [url]
  7. N. D. Vanli, M. O. Sayin, et al., “Nonlinear Regression via Incremental Decision Trees,” Pattern Recognition, 2019. [url]
  8. O. F. Kilic, T. Ergen, M. O. Sayin, and S. S. Kozat, “Team-Optimal Online Estimation of Dynamic Parameters over Distributed Tree Networks,” Signal Process., 2019. [url]
  9. M. O. Sayin, et al., “Stochastic Subgradient Algorithms for Strongly Convex Optimization over Distributed Networks,” IEEE Trans. Netw. Sci. Eng., 2017. [url][Runner-up of the 2019 IEEE TNSE Best Paper Award]
  10. M. O. Sayin, S. S. Kozat,  and T. Başar, “Team-Optimal Distributed MMSE Estimation in General and Tree Networks,” Digital Signal Process., 2017. [url]
  11. D. Kari, I. Marivani, F. Khan, M. O. Sayin, and S. S. Kozat, “Robust Adaptive Algorithms for Underwater Acoustic Channel Estimation and Their Performance Analysis,” Digital Signal Process., 2017. [url]
  12. N. D. Vanli, M. O. Sayin, et al., “Sequential Nonlinear Learning for Distributed Multi-Agent Systems via Extreme Learning Machines,” IEEE Trans. Neural Net. Learn. Syst., 2017. [url]
  13. N. D. Vanli, K. Gokcesu, M. O. Sayin, et al., “Sequential Prediction Over Hierarchical Structures,” IEEE Trans. Signal Process., 2016. [url]
  14. O. F. Kilic, M. O. Sayin, et al., “Computationally Highly Efficient Mixture of Adaptive Filters,” Signal Image Video Process., 2016. [url]
  15. M. O. Sayin, et al., “Krylov Proportionate Normalized Least Mean Fourth Approach: Formulation and Performance Analysis,” Signal Process., 2015. [url]
  16. M. O. Sayin and S. S. Kozat, “Compressive Diffusion Strategies Over Distributed Networks for Reduced Communication Load,” IEEE Trans. Signal Process., 2014. [url]
  17. M. O. Sayin, N. D. Vanli, and S. S. Kozat, “A Novel Family of Adaptive Filtering Algorithms Based on the Logarithmic Cost,” IEEE Trans. Signal Process., 2014. [url]
  18. M. O. Sayin and S. S. Kozat, “Single Bit and Reduced Dimension Diffusion Strategies Over Distributed Networks,” IEEE Signal Process. Lett., 2013. [url]

Chapters in Edited Volumes

  1. M. O. Sayin and T. Başar. Deception-As-Defense Framework for Cyber-Physical Systems. In Safety, Security, and Privacy for Cyber-Physical Systems, Springer, 2021. [url]
  2. M. O. Sayin, et al. Minimax Detection (MAD) for Computer Security: A Dynamic Program Characterization. In Game Theory and Machine Learning for Cyber Security, John Wiley & Sons, 2021. [url]

Patents

  1. M. O. Sayin, C.-W. Lin, S. Shiraishi, “Managing Roadway Intersections for Vehicles,” US Patent US11151869B2, Granted on Oct. 19, 2021. [url]

Conferences

  1. O. Unlu and M. O. Sayin. Episodic logit-Q dynamics for efficient learning in stochastic teams. In IEEE CDC, 2023. [url]
  2. S.-C. Huang, K.-E. Lin, C.-Y. Kuo, L.-H. Lin, M. O. Sayin, and C.-W. Lin, “Reinforcement-learning-based job-shop scheduling for intelligent intersection management,” in Design, Automation and Test in Europe Conference (DATE), 2023.
  3. M. O. Sayin, “On the global convergence of stochastic fictitious play in stochastic games with turn-based controllers”, in IEEE CDC, 2022. [url]
  4. A. Ozdaglar, M. O. Sayin and K. Zhang. Independent Learning in Stochastic Games. in the Proceedings of the International Congress of Mathematicians (ICM’22), vol. 7, pp. 5340-5373, 2022. [url]
  5. M. O. Sayin, K. Zhang, and A. Ozdaglar, “Fictitious Play in Markov Games with Single Controller,” in ACM EC, 2022. [url]
  6. M. O. Sayin and K. A. Cetiner, “On the Heterogeneity of Independent Learning Dynamics in Zero-sum Stochastic Games”, in L4DC, 2022. [pdf][url][poster]
  7. M. O. Sayin*, K. Zhang*, D. S. Leslie, T. Başar, and A. Ozdaglar, “Decentralized Q-learning in Zero-sum Markov Games,” in NeurIPS, 2021. [url] [poster]
  8. M. O. Sayin*, K. Zhang*, D. S. Leslie, T. Başar, and A. Ozdaglar, “Decentralized Q-learning in Zero-sum Markov Games,” in Workshop on Reinforcement Learning Theory at ICML, 2021.
  9. M. O. Sayin and T. Başar, “On the Optimality of Linear Signaling to Deceive Kalman Filters Over Finite/Infinite Horizons,” in GameSec, 2019. [pdf][url]
  10. M. O. Sayin, et al., “A Game Theoretical Framework for Inter-Process Adversarial Intervention Detection,” in GameSec, 2018. [url]
  11. M. O. Sayin and T. Başar, “Dynamic Information Disclosure for Deception,” in IEEE CDC, 2018. [pdf][url]
  12. M. O. Sayin and T. Başar, “Secure Sensor Design for Resiliency of Control Systems Prior to Attack Detection,” in IEEE CCTA, 2018. [pdf][url]
  13. M. O. Sayin and T. Başar, “Deceptive Multi-dimensional Information Disclosure over a Gaussian Channel,” in ACC, 2018. [pdf][url]
  14. M. O. Sayin, et al., “Reliable Intersection Control in Non-cooperative Environments,” in ACC, 2018.[url]
  15. B. Zheng, M. O. Sayin, et al., “Timing and Security Analysis of VANET-based Intelligent Transportation Systems,” in IEEE ICCAD, 2017. [url]
  16. M. O. Sayin and T. Başar, “Secure Sensor Design for Cyber-Physical Systems Against Advanced Persistent Threats,” in GameSec, 2017. [pdf][url]
  17. M. O. Sayin, E. Akyol, and T. Başar, “Strategic Control of a Tracking System,” in IEEE CDC, 2016. [pdf][url]
  18. M. O. Sayin, E. Akyol, and T. Başar, “On the Structure of Equilibrium Strategies in Dynamic Gaussian Signaling Games,” in IEEE MSC, 2016.[url]
  19. O. F. Kilic, M. O. Sayin, et al., “Mixture of Set Membership Filters Approach for Big Data Signal Processing,” in IEEE SIU, 2016. [url] [Best Student Paper Award]
  20. M. O. Sayin, et al., “Efficient and Distributed Tracking of Evolving State,” in IEEE MLSP, 2015.[url]
  21. N. D. Vanli, M. O. Sayin, I. Delibalta, and S. S. Kozat, “Universal Online Prediction via Order Preserving Patterns,” in IEEE MLSP, 2015.[url]
  22. M. O. Sayin, et al., “Optimal and Efficient Distributed Online Learning for Big Data,” in IEEE Big Data Congress, 2015.[url]
  23. N. D. Vanli, M. O. Sayin, and S. S. Kozat, “Twice-Universal Piecewise Linear Regression via Infinite Depth Context Trees,” in IEEE ICASSP, 2015.[url]
  24. M. O. Sayin, et al., “Communication Efficient Channel Estimation Over Distributed Networks,” in IEEE GlobalSIP, 2014.[url]
  25. N. D. Vanli, M. O. Sayin, T. Goze, and S. S. Kozat, “Energy Consumption Forecasting via Order Preserving Pattern Matching,” in IEEE GlobalSIP, 2014.[url]
  26. N. D. Vanli, M. O. Sayin, S. Ergut, and S. S. Kozat, “Piecewise Nonlinear Regression via Decision Adaptive Trees,” in EUSIPCO, 2014.[url]
  27. N. D. Vanli, M. O. Sayin, S. Ergut, and S. S. Kozat, “Comprehensive Lower Bounds on Sequential Prediction,” in EUSIPCO, 2014.[url]
  28. M. O. Sayin, N. D. Vanli, and S. S. Kozat, “Logarithmic Regret Bound Over Diffusion Based Distributed Estimation,” in IEEE ICASSP, 2014.[url]
  29. M. O. Sayin, N. D. Vanli, and S. S. Kozat, “Improved Convergence Performance of Adaptive Algorithms Through Logarithmic Cost,” in IEEE ICASSP, 2014.[url]
  30. M. O. Sayin, N. D. Vanli, and S. S. Kozat, “Robust Set-Membership Filtering Algorithms Against Impulsive Noise,” in IEEE SIU, 2014.[url]
  31. M. O. Sayin, N. D. Vanli, and S. S. Kozat, “Performance Analysis of Scalar Diffusion Strategy Over Distributed Networks,” in IEEE SIU, 2014.[url]
  32. N. D. Vanli, M. O. Sayin, and S. S. Kozat, “Competitive Linear MMSE Estimation Under Structured Data Uncertainties,” in IEEE SIU, 2014.[url]