
Homepage of Lun ZHANG
I am a professor of mathematics in the School of Mathematical Sciences at Fudan University.
张仑 - Fudan University
基本信息姓名张仑英文名:Zhang,lun职称:教授(博士生导师)研究方向:Riemann-Hilbert问题,随机矩阵,渐进分析,逼近论主讲课程:代表论著:个人主页:http://homepage.fudan.edu.cn/lunzhang
Lun Zhang - Google Scholar
School of Mathematical Sciences, Fudan University - Cited by 939 - Riemann-Hilbert problems and asymptotic analysis - random matrices - (multiple) orthogonal polynomials and special functions
Zhan-Lun Chang - Google Scholar
Purdue University - Cited by 38 - Wireless Communication - Resource Allocation - Game Theory - Edge Computing - Federated Learning
Zhan-Lun Chang - Research Assistant - Purdue University | LinkedIn
2021年4月15日 · I am actively looking for 2025 Spring/Summer AI/ML Research Internship. I am a Ph.D. student at Purdue University, advised by Prof. Christopher G. Brinton and President Mung Chiang. My research...
GitHub Pages - Zhan Ling
Currently, my primary goal is to create an LLM/VLM-based reasoning agent capable of achieving superhuman performance on challenging problems, such as solving advanced math and coding problems. Papers sorted by recency (*/**/*** = equal contribution). Representative papers are …
zhang lun - Google 学术搜索
Computer Vision–ACCV 2018: 14th Asian Conference on Computer Vision, Perth … HAN Jinglu, C Zhang, Y Cai, Y Zhu, P Dong, B Qiang, QI Yitong, Z Lin, ...
张仑 - Fudan University
姓名 张仑 英文名: Zhang, lun 职称: 副研究员 办公室: 2122 办公电话: 021-55665565 E-mail: [email protected] 研究方向: Riemann-Hilbert问题,随机矩阵,渐进分析,逼近 …
【Prof. Lun Zhang(张伦)】-北京大学新闻与传播学院
Lun Zhang is currently an associate professor at Beijing Normal University. She obtained her PhD degree in communication (2011) from City University of Hong Kong. Her current research projects...
Federated Learning with Dynamic Client Arrival and Departure:...
Building on our probabilistic framework that provides direct insights into how the arrival and departure of different types of clients influence the shifts in optimal points, we establish an upper bound on the optimality gap, accounting for factors such as stochastic gradient noise, local training iterations, non-IIDness of data distribution, an...