Yardim, Batuhan

7 publications

L4DC 2025 Exploiting Approximate Symmetry for Efficient Multi-Agent Reinforcement Learning Batuhan Yardim, Niao He

NeurIPS 2025 Scalable Neural Incentive Design with Parameterized Mean-Field Approximation Nathan Corecco, Batuhan Yardim, Vinzenz Thoma, Zebang Shen, Niao He

ICMLW 2024 Exploiting Approximate Symmetry for Efficient Multi-Agent Reinforcement Learning Batuhan Yardim, Niao He

AISTATS 2024 On the Statistical Efficiency of Mean-Field Reinforcement Learning with General Function Approximation Jiawei Huang, Batuhan Yardim, Niao He

ICMLW 2024 When Is Mean-Field Reinforcement Learning Tractable and Relevant? Batuhan Yardim, Artur Goldman, Niao He

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

NeurIPS 2022 Trust Region Policy Optimization with Optimal Transport Discrepancies: Duality and Algorithm for Continuous Actions Antonio Terpin, Nicolas Lanzetti, Batuhan Yardim, Florian Dorfler, Giorgia Ramponi