Chen, Ziang

13 publications

NeurIPS 2025 Evaluating Generalization Capabilities of LLM-Based Agents in Mixed-Motive Scenarios Using Concordia Chandler Smith, Marwa Abdulhai, Manfred Diaz, Marko Tesic, Rakshit Trivedi, Sasha Vezhnevets, Lewis Hammond, Jesse Clifton, Minsuk Chang, Edgar A. Duéñez-Guzmán, John P Agapiou, Jayd Matyas, Danny Karmon, Beining Zhang, Jim Dilkes, Akash Kundu, Jord Nguyen, Emanuel Tewolde, Jebish Purbey, Ram Mohan Rao Kadiyala, Siddhant Gupta, Aliaksei Korshuk, Buyantuev Alexander, Ilya Makarov, Gang Zhao, Rolando Fernandez, Zhihan Wang, Caroline Wang, Jiaxun Cui, Lingyun Xiao, Di Yang Shi, Yoonchang Sung, Arrasy Rahman, Peter Stone, Yipeng Kang, Hyeonggeun Yun, Ananya Ananya, Taehun Cha, Zhiqiang Wu, Elizaveta Tennant, Olivia Macmillan-Scott, Marta Emili García Segura, Diana Riazi, Fuyang Cui, Sriram Ganapathi Subramanian, Toryn Q. Klassen, Nico Schiavone, Mogtaba Alim, Sheila A. McIlraith, Manuel Sebastian Rios Beltran, Oswaldo Peña, Carlos Saith Rodriguez Rojas, Manuela Chacon-Chamorro, Ruben Manrique, Luis Felipe Giraldo, Nicanor Quijano, Yiding Wang, Yuxuan Chen, Fangwei Zhong, Mengmeng Wang, Wenming Tu, Zhaowei Zhang, Ziang Chen, Zixia Jia, Xue Feng, Zilong Zheng, Chichen Lin, Weijian Fan, Chenao Liu, Sneheel Sarangi, Ziyan Wang, Shuqing Shi, Yali Du, Avinaash Anand Kulandaivel, Yang Liu, Wu Ruiyang, Chetan Talele, 陆孙嘉, Gema Parreño Piqueras, Shamika Dhuri, Bain McHale, Tim Baarslag, Dylan Hadfield-Menell, Natasha Jaques, Jose Hernandez-Orallo, Joel Z Leibo

ICML 2025 Expressive Power of Graph Neural Networks for (Mixed-Integer) Quadratic Programs Ziang Chen, Xiaohan Chen, Jialin Liu, Xinshang Wang, Wotao Yin

ICLR 2025 On Designing General and Expressive Quantum Graph Neural Networks with Applications to MILP Instance Representation Xinyu Ye, Hao Xiong, Jianhao Huang, Ziang Chen, Jia Wang, Junchi Yan

NeurIPS 2024 Certified Machine Unlearning via Noisy Stochastic Gradient Descent Eli Chien, Haoyu Wang, Ziang Chen, Pan Li

ICML 2024 Efficient Algorithms for Sum-of-Minimum Optimization Lisang Ding, Ziang Chen, Xinshang Wang, Wotao Yin

ICLRW 2024 Langevin Unlearning Eli Chien, Haoyu Peter Wang, Ziang Chen, Pan Li

NeurIPS 2024 Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning Eli Chien, Haoyu Wang, Ziang Chen, Pan Li

NeurIPS 2024 Mean-Field Analysis for Learning Subspace-Sparse Polynomials with Gaussian Input Ziang Chen, Rong Ge

NeurIPS 2024 Rethinking the Capacity of Graph Neural Networks for Branching Strategy Ziang Chen, Jialin Liu, Xiaohan Chen, Xinshang Wang, Wotao Yin

AISTATS 2023 HeteRSGD: Tackling Heterogeneous Sampling Costs via Optimal Reweighted Stochastic Gradient Descent Ziang Chen, Jianfeng Lu, Huajie Qian, Xinshang Wang, Wotao Yin

ICLR 2023 On Representing Linear Programs by Graph Neural Networks Ziang Chen, Jialin Liu, Xinshang Wang, Wotao Yin

ICLR 2023 On Representing Mixed-Integer Linear Programs by Graph Neural Networks Ziang Chen, Jialin Liu, Xinshang Wang, Wotao Yin

NeurIPS 2021 On the Representation of Solutions to Elliptic PDEs in Barron Spaces Ziang Chen, Jianfeng Lu, Yulong Lu