Deren Han

2.6k total citations
96 papers, 1.7k citations indexed

About

Deren Han is a scholar working on Computational Mechanics, Numerical Analysis and Computational Theory and Mathematics. According to data from OpenAlex, Deren Han has authored 96 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Computational Mechanics, 55 papers in Numerical Analysis and 50 papers in Computational Theory and Mathematics. Recurrent topics in Deren Han's work include Sparse and Compressive Sensing Techniques (55 papers), Advanced Optimization Algorithms Research (55 papers) and Optimization and Variational Analysis (35 papers). Deren Han is often cited by papers focused on Sparse and Compressive Sensing Techniques (55 papers), Advanced Optimization Algorithms Research (55 papers) and Optimization and Variational Analysis (35 papers). Deren Han collaborates with scholars based in China, Hong Kong and Singapore. Deren Han's co-authors include Xiaoming Yuan, Bingsheng He, Hai Yang, Xingju Cai, Li‐Zhi Liao, Tingting Wu, Kun Guo, Liwei Zhang, Defeng Sun and Yang Wei and has published in prestigious journals such as European Journal of Operational Research, IEEE Access and Mathematics of Computation.

In The Last Decade

Deren Han

83 papers receiving 1.6k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Deren Han China 21 1.0k 733 680 232 231 96 1.7k
Ting Kei Pong Hong Kong 18 806 0.8× 539 0.7× 522 0.8× 228 1.0× 147 0.6× 54 1.4k
Min Tao China 15 868 0.9× 333 0.5× 263 0.4× 355 1.5× 136 0.6× 48 1.2k
Naihua Xiu China 24 558 0.5× 1.1k 1.5× 1.2k 1.8× 182 0.8× 104 0.5× 124 2.0k
Patrick Redont France 14 786 0.8× 616 0.8× 770 1.1× 201 0.9× 416 1.8× 18 1.5k
Yangyang Xu United States 18 1.4k 1.4× 355 0.5× 313 0.5× 793 3.4× 120 0.5× 72 2.5k
Aris Daniilidis France 18 598 0.6× 665 0.9× 972 1.4× 132 0.6× 267 1.2× 51 1.6k
Brendan O’Donoghue United States 12 549 0.5× 283 0.4× 275 0.4× 262 1.1× 100 0.4× 20 1.6k
Bernard Mourrain France 28 1.5k 1.5× 282 0.4× 1.3k 1.9× 343 1.5× 37 0.2× 157 3.0k
Jérôme Malick France 17 378 0.4× 451 0.6× 482 0.7× 111 0.5× 66 0.3× 46 1.0k
Zhi-Quan Luo United States 13 717 0.7× 294 0.4× 251 0.4× 272 1.2× 78 0.3× 22 2.3k

Countries citing papers authored by Deren Han

Since Specialization
Citations

This map shows the geographic impact of Deren Han's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Deren Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deren Han more than expected).

Fields of papers citing papers by Deren Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Deren Han. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Deren Han. The network helps show where Deren Han may publish in the future.

Co-authorship network of co-authors of Deren Han

This figure shows the co-authorship network connecting the top 25 collaborators of Deren Han. A scholar is included among the top collaborators of Deren Han based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Deren Han. Deren Han is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
He, Hongjin, et al.. (2025). Practical proximal primal-dual algorithms for structured saddle point problems. Journal of Global Optimization. 93(3). 803–831.
2.
Cui, Chunfeng, et al.. (2025). Convergence of Three-Block ADMM for Weakly Convex Optimization Problems. SIAM Journal on Imaging Sciences. 18(1). 449–493. 1 indexed citations
3.
Yu, Dongmei, et al.. (2025). Predefined-time robust gradient neural network for solving absolute value equations. Journal of Computational and Applied Mathematics. 473. 116887–116887.
4.
Wu, Shi-Liang, Deren Han, & Cui-Xia Li. (2024). A class of maximum-based iteration methods for the generalized absolute value equation. Applied Mathematics Letters. 156. 109139–109139. 2 indexed citations
5.
Liu, Zehui, et al.. (2024). A Bregman Proximal Stochastic Gradient Method with Extrapolation for Nonconvex Nonsmooth Problems. Proceedings of the AAAI Conference on Artificial Intelligence. 38(14). 15580–15588. 3 indexed citations
6.
Zeng, Yun, et al.. (2024). On Adaptive Stochastic Heavy Ball Momentum for Solving Linear Systems. SIAM Journal on Matrix Analysis and Applications. 45(3). 1259–1286. 7 indexed citations
7.
Cui, Chunfeng, et al.. (2024). A Momentum Accelerated Algorithm for ReLU-Based Nonlinear Matrix Decomposition. IEEE Signal Processing Letters. 31. 2865–2869. 1 indexed citations
8.
Han, Deren, et al.. (2023). Multi-step inertial strictly contractive PRSM algorithms for convex programming problems with applications. Journal of Computational and Applied Mathematics. 437. 115469–115469. 1 indexed citations
9.
Tang, Jia, et al.. (2023). On finite termination of the generalized Newton method for solving absolute value equations. Computational and Applied Mathematics. 42(4). 4 indexed citations
10.
He, Hongjin, et al.. (2023). A Partially Inertial Customized Douglas–Rachford Splitting Method for a Class of Structured Optimization Problems. Journal of Scientific Computing. 98(1). 2 indexed citations
11.
Cui, Chunfeng, et al.. (2023). Accelerated Doubly Stochastic Gradient Descent for Tensor CP Decomposition. Journal of Optimization Theory and Applications. 197(2). 665–704. 4 indexed citations
12.
Yu, Dongmei, et al.. (2023). A new relaxed acceleration two-sweep modulus-based matrix splitting iteration method for solving linear complementarity problems. AIMS Mathematics. 8(6). 13368–13389. 1 indexed citations
13.
Cai, Xingju, et al.. (2020). The convergence rate analysis of the symmetric ADMM for the nonconvex separable optimization problems. Journal of Industrial and Management Optimization. 17(4). 1943–1943. 9 indexed citations
14.
Han, Deren, Defeng Sun, & Liwei Zhang. (2017). Linear Rate Convergence of the Alternating Direction Method of Multipliers for Convex Composite Programming. Mathematics of Operations Research. 43(2). 622–637. 77 indexed citations
15.
Cai, Xingju, et al.. (2017). Comparison of several fast algorithms for projection onto an ellipsoid. Journal of Computational and Applied Mathematics. 319. 320–337. 10 indexed citations
16.
Han, Deren, et al.. (2012). Efficient neural networks for solving variational inequalities. Neurocomputing. 86. 97–106. 9 indexed citations
17.
Han, Deren, et al.. (2006). Atomic Splitable Selfish Routing with Polynomial Cost Functions. Networks and Spatial Economics. 7(2). 2 indexed citations
18.
Han, Deren & Hong K. Lo. (2002). A new stepsize rule in He and Zhou's alternating direction method. Applied Mathematics Letters. 15(2). 181–185. 10 indexed citations
19.
Han, Deren & Bingsheng He. (2001). A New Accuracy Criterion for Approximate Proximal Point Algorithms. Journal of Mathematical Analysis and Applications. 263(2). 343–354. 48 indexed citations
20.
Han, Deren & Hong K. Lo. (2000). A new modified extra-gradient method for variational inequality problems. Neural, Parallel & Scientific Computations archive. 8(3). 401–414. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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