I am an NSF TRIPODS Postdoctoral Fellow at the University of Illinois at Urbana-Champaign. I am affiliated with Illinois Institute of Data Science and Dynamical Systems. My research interests lie in theoretical machine learning, optimization and applied probability, with a focus on:
My curriculum vitae can be found here. |
Selected Papers
- Finite-Time Analysis of Entropy-Regularized Neural Natural Actor-Critic [paper]
Semih Cayci, Niao He, R. Srikant
To be presented in International Conference on Continuous Optimization 2022 - Sample Complexity and Overparameterization Bounds for TD Learning with Neural Network Approximation [paper]
Semih Cayci, Siddhartha Satpathi, Niao He, R. Srikant
ICML Workshop on Overparameterization 2021 - 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
Semih Cayci, Yilin Zheng, Atilla Eryilmaz
AAAI 2022
[paper] - Group-Fair Online Allocation in Continuous Time
Semih Cayci, Swati Gupta, Atilla Eryilmaz
NeurIPS 2020
[paper] - Budget-Constrained Bandits over General Cost and Reward Distributions
Semih Cayci, Atilla Eryilmaz, R. Srikant
AISTATS 2020
[paper] - Learning to Control Renewal Processes with Bandit Feedback
Semih Cayci, Atilla Eryilmaz, R. Srikant
ACM SIGMETRICS 2019
[paper]