邓琪
系别:数据与商务智能系
职称:副教授
办公电话:52301593
电子邮箱:qdeng24@sjtu.edu.cn
教师简介:
邓琪,现任上海交通大学安泰经济与管理学院副教授,(办公室在浩然大厦815)此前在上海财经大学信息管理与工程学院工作,分别担任助理教授和副教授。分别于美国佛罗里达大学和上海交通大学获得计算机专业博士和学士学位。主要研究兴趣包括数学规划和机器学习。近年来的研究成果发表在 Math Programming, IJOC, POMS, NeurIPS, ICML 等管理、优化与机器学习领域的期刊和会议上。
研究兴趣: 随机、非光滑与约束优化的算法与复杂度理论; 联合预测与优化的集成模型;能源与电力系统中的应用
近期相关工作:
Lin, Z. & Deng, Q. (2024) Faster Accelerated First-order Methods for Convex Optimization with Strongly Convex Function Constraints. NeurIPS 2024
Deng, Q., Feng, Q., Gao, W., Ge, D., Jiang, B., Jiang, Y., Liu, J., Liu, T., Xue, C., & Ye, Y. (2024). An Enhanced ADMM-based Interior Point Method for Linear and Conic Optimization. Informs Journal on Computing.
Lin, Z., Xue, C., Deng, Q., & Ye, Y. (2024). A Single-Loop Robust Policy Gradient Method for Robust Markov Decision Processes. ICML 2024. ing
Processes
Gao, W., & Deng, Q. (2024). Stochastic Weakly Convex Optimization Beyond Lipschitz Continuity. ICML 2024
Tan, J., Xue, C., Zhang, C., Deng, Q., Ge, D., & Ye, Y. (2024). A Homogenization Approach for Gradient-Dominated Stochastic Optimization.UAI 2024.
Xie, C., Li, C., Zhang, C., Deng, Q., Ge, D., & Ye, Y. (2024). Trust region methods for nonconvex stochastic optimization beyond Lipschitz smoothness. Proceedings of the AAAI Conference on Artificial Intelligence,
Liu, J., Xie, C., Deng, Q., Ge, D., & Ye, Y. (2024). Sketched Newton Value Iteration for Large-Scale Markov Decision Processes. Proceedings of the AAAI Conference on Artificial Intelligence,
主讲课程:数据结构 (计划)