Polar code construction for non-binary source alphabets. - Semih Cayci; Orhan Arikan; Erdal Arikan (SIU, 2012)

Lossless polar compression of g-ary sources. - Semih Cayci; Orhan Arikan (ISIT, 2013)

On the Multi-Channel Capacity Gains of Millimeter-Wave Communication. - Semih Cayci; Atilla Eryilmaz (GLOBECOM, 2016)

Learning for serving deadline-constrained traffic in multi-channel wireless networks. - Semih Cayci; Atilla Eryilmaz (WiOpt, 2017)

Nonbinary Polar Coding for Multilevel Modulation. - Semih Cayci; Toshiaki Koike-Akino; Ye Wang 001 (OFC, 2019)

Hardware-Efficient Quantized Polar Decoding with Optimized Lookup Table. - Toshiaki Koike-Akino; Ye Wang 001; Semih Cayci; David S. Millar; Keisuke Kojima; Kieran Parsons (OECC/PSC, 2019)

Learning to Control Renewal Processes with Bandit Feedback. - Semih Cayci; Atilla Eryilmaz; R. Srikant 001 (Proc. ACM Meas. Anal. Comput. Syst., 2019)

Optimal Learning for Dynamic Coding in Deadline-Constrained Multi-Channel Networks. - Semih Cayci; Atilla Eryilmaz (IEEE/ACM Trans. Netw., 2019)

Budget-Constrained Bandits over General Cost and Reward Distributions. - Semih Cayci; Atilla Eryilmaz; R. Srikant 001 (AISTATS, 2020)

Group-Fair Online Allocation in Continuous Time. - Semih Cayci; Swati Gupta 001; Atilla Eryilmaz (NeurIPS, 2020)

Continuous-Time Multi-Armed Bandits with Controlled Restarts. - Semih Cayci; Atilla Eryilmaz; R. Srikant 001 (CoRR, 2020)

Sample Complexity and Overparameterization Bounds for Projection-Free Neural TD Learning. - Semih Cayci; Siddhartha Satpathi; Niao He; R. Srikant 001 (CoRR, 2021)

Linear Convergence of Entropy-Regularized Natural Policy Gradient with Linear Function Approximation. - Semih Cayci; Niao He; R. Srikant 001 (CoRR, 2021)

A Lyapunov-Based Methodology for Constrained Optimization with Bandit Feedback. - Semih Cayci; Yilin Zheng; Atilla Eryilmaz (AAAI, 2022)

Learning to Control Partially Observed Systems with Finite Memory. - Semih Cayci; Niao He; R. Srikant 001 (CoRR, 2022)

Policy Mirror Ascent for Efficient and Independent Learning in Mean Field Games. - Batuhan Yardim; Semih Cayci; Matthieu Geist; Niao He (ICML, 2023)

Provably Robust Temporal Difference Learning for Heavy-Tailed Rewards. - Semih Cayci; Atilla Eryilmaz (NeurIPS, 2023)

Sample Complexity and Overparameterization Bounds for Temporal-Difference Learning With Neural Network Approximation. - Semih Cayci; Siddhartha Satpathi; Niao He; R. Srikant 001 (IEEE Trans. Autom. Control., 2023)

Convergence of Gradient Descent for Recurrent Neural Networks: A Nonasymptotic Analysis. - Semih Cayci; Atilla Eryilmaz (CoRR, 2024)

Recurrent Natural Policy Gradient for POMDPs. - Semih Cayci; Atilla Eryilmaz (CoRR, 2024)

Essentially Sharp Estimates on the Entropy Regularization Error in Discrete Discounted Markov Decision Processes. - Johannes Müller; Semih Cayci (CoRR, 2024)

Gauss-Newton Dynamics for Neural Networks: A Riemannian Optimization Perspective. - Semih Cayci (CoRR, 2024)

Convergence of Entropy-Regularized Natural Policy Gradient with Linear Function Approximation. - Semih Cayci; Niao He; R. Srikant 001 (SIAM J. Optim., 2024)

Finite-Time Analysis of Natural Actor-Critic for POMDPs. - Semih Cayci; Niao He; R. Srikant 001 (SIAM J. Math. Data Sci., 2024)

Finite-Time Analysis of Entropy-Regularized Neural Natural Actor-Critic Algorithm. - Semih Cayci; Niao He; R. Srikant 001 (Trans. Mach. Learn. Res., 2024)

Fast Online Learning of Vulnerabilities for Networks With Propagating Failures. - Yilin Zheng; Semih Cayci; Atilla Eryilmaz (IEEE/ACM Trans. Netw., 2024)

Fisher-Rao Gradient Flows of Linear Programs and State-Action Natural Policy Gradients. - Johannes Müller; Semih Cayci; Guido Montúfar (SIAM J. Optim., 2025)

Budgeted-Bandits with Controlled Restarts with Applications in Learning and Computing. - Semih Cayci; Yilin Zheng; Atilla Eryilmaz (Trans. Mach. Learn. Res., 2025)

A Variational Inequality Approach to Independent Learning in Static Mean-Field Games. - Batuhan Yardim; Semih Cayci; Niao He (CoRR, 2025)