Research
IEOR researchers investigate the latest mathematical tools, approaches, and methodologies to make new theoretical discoveries and innovations that touch nearly every industry, making them more efficient and profitable in areas such as supply chain, logistics, manufacturing, data science, energy systems, robotics, and management.
Selected Publications
Improving Toponym Resolution by Predicting Attributes to Constrain Geographical Ontology Entries
Zhang, Zeyu & Laparra, Egoitz & Bethard, Steven. (2024). Improving Toponym Resolution by Predicting Attributes to Constrain Geographical Ontology Entries. 35-44. 10.18653/v1/2024.naacl-short.3.
Auto- Train-Once: Controller Network Guided Automatic Network Pruning from Scratch
Wu, Xidong & Gao, Shangqian & Zhang, Zeyu & Li, Zhenzhen & Bao, Runxue & Zhang, Yanfu & Wang, Xiaoqian & Huang, Heng. (2024). Auto- Train-Once: Controller Network Guided Automatic Network Pruning from Scratch. 16163-16173. 10.1109/CVPR52733.2024.01530.
Reinforcement Learning from Answer Reranking Feedback for Retrieval-Augmented Answer Generation
Nguyen, Minh & Nguyen, Toan & KC, Kishan & Zhang, Zeyu & Vu, Thuy. (2024). Reinforcement Learning from Answer Reranking Feedback for Retrieval-Augmented Answer Generation. 4044-4048. 10.21437/Interspeech.2024-2147.
On the Softplus Penalty for Large-Scale Convex Optimization
Li, Meng & Grigas, Paul & Atamtürk, Alper. (2023). On the Softplus Penalty for Large-Scale Convex Optimization. Operations Research Letters. 51. 10.1016/j.orl.2023.10.015.