Semih Cayci
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I am a tenure-track Assistant Professor for Mathematics of Machine Learning in the Department of Mathematics at RWTH Aachen University.

My research interests lie in theoretical machine learning, optimization and probability theory, with a focus on:
  • theoretical and algorithmic foundations of reinforcement learning,
  • deep learning theory,
  • online learning and bandits.


Selected Papers
  • Sample Complexity and Overparameterization Bounds for TD Learning with Neural Network Approximation [paper]
    Semih Cayci, Siddhartha Satpathi, Niao He, R. Srikant
    IEEE Transactions on Automatic Control, May 2023.
  • Convergence of Entropy-Regularized Natural Policy Gradient Methods with Linear Function Approximation [paper]
    Semih Cayci, Niao He, R. Srikant
    ICML Workshop on Reinforcement Learning Theory 2021
  • A Lyapunov-Based Methodology for Constrained Optimization with Bandit Feedback [paper]
    Semih Cayci, Yilin Zheng, Atilla Eryilmaz
    AAAI 2022
Teaching
  • MATH 11.70010 - Mathematical Foundations of Reinforcement Learning (Winter 2022/23)
Miscellaneous
  • Prior to joining RWTH Aachen, I was an NSF TRIPODS Postdoctoral Fellow at the University of Illinois at Urbana-Champaign. I was affiliated with Illinois Institute of Data Science and Dynamical Systems and ODI Group at ETH Zurich.
  • I received my PhD from the Ohio State University.
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