Jinlan Liu - RankMe

35 papers Misc 1Journal 26Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A novel parameter-free filled function method for global optimization and solving nonlinear equation systems. J. Frankl. Inst. Jinlan Liu, Helei Kang, Renyun Liu, Dongpo Xu
2026	J	`jnl`	A random reshuffling method for generalized Sylvester quaternion matrix equations. J. Comput. Appl. Math. Qiankun Diao, Yiming Jiang, Jinlan Liu, Dongpo Xu
2026	J	`jnl`	An efficient low-complexity stochastic BFGS algorithm using matrix diagonal approximations for nonconvex optimization in machine learning. J. Comput. Appl. Math. Hanger Liu, Jinlan Liu, Naimin Zhang, Dongpo Xu
2026	J	`jnl`	SSR1M: A stochastic SR1 method with momentum acceleration for non-Convex optimization. Neural Networks Jinlan Liu, Hanger Liu, Xin Deng, Dongpo Xu
2025	J	`jnl`	A robust stochastic quasi-Newton algorithm for non-convex machine learning. Appl. Intell. Hanger Liu, Yuqing Liang, Jinlan Liu, Dongpo Xu
2025	J	`jnl`	AdaVAM: Adaptive variance-aware momentum for accelerating deep neural network training. Knowl. Based Syst. Jinlan Liu, Wenhan Jiang, Xin Deng, Dongpo Xu
2025	J	`jnl`	Convergence of Adam for non-convex objectives: relaxed hyperparameters and non-ergodic case. Mach. Learn. Yuqing Liang, Meixuan He, Jinlan Liu, Dongpo Xu
2025	J	`jnl`	DMAdam: Dual averaging enhanced adaptive gradient method for deep neural networks. Knowl. Based Syst. Wenhan Jiang, Jinlan Liu, Naimin Zhang, Dongpo Xu
2025	J	`jnl`	Iterative methods for the generalized Sylvester quaternion matrix equations using the ADMM approach. J. Frankl. Inst. Qiankun Diao, Jinlan Liu, Hongmei Shao, Dongpo Xu
2025	J	`jnl`	On the Convergence of Decentralized Stochastic Gradient Descent With Biased Gradients. IEEE Trans. Signal Process. Yiming Jiang, Helei Kang, Jinlan Liu, Dongpo Xu
2025	J	`jnl`	Sharpness-Aware Minimization method with momentum acceleration for deep neural networks. Knowl. Based Syst. Helei Kang, Yiming Jiang, Jinlan Liu, Dongpo Xu
2024	J	`jnl`	An Iterative Algorithm for Quaternion Eigenvalue Problems in Signal Processing. IEEE Signal Process. Lett. Qiankun Diao, Jinlan Liu, Naimin Zhang, Dongpo Xu
2024	J	`jnl`	ColorMesh: Surface and texture reconstruction of large-scale scenes from unstructured colorful point clouds with adaptive automatic viewpoint selection. Int. J. Appl. Earth Obs. Geoinformation Mubai Li, Zhenxin Zhang, Siyun Chen, Liqiang Zhang, Zhihua Xu, Xiaoxu Ren, Jinlan Liu, Peng Sun
2024	J	`jnl`	Shuffling-type gradient method with bandwidth-based step sizes for finite-sum optimization. Neural Networks Yuqing Liang, Yang Yang, Jinlan Liu, Dongpo Xu
2024	J	`jnl`	UAdam: Unified Adam-Type Algorithmic Framework for Nonconvex Optimization. Neural Comput. Yiming Jiang, Jinlan Liu, Dongpo Xu, Danilo P. Mandic
2024	J	`jnl`	mPage: Probabilistic Gradient Estimator With Momentum for Non-Convex Optimization. IEEE Trans. Signal Process. Yuqing Liang, Hui Su, Jinlan Liu, Dongpo Xu
2023	J	`jnl`	Convergence of Adam for Non-convex Objectives: Relaxed Hyperparameters and Non-ergodic Case. CoRR Meixuan He, Yuqing Liang, Jinlan Liu, Dongpo Xu
2023	J	`jnl`	Last-iterate convergence analysis of stochastic momentum methods for neural networks. Neurocomputing Jinlan Liu, Dongpo Xu, Yinghua Lu, Jun Kong, Danilo P. Mandic
2023	J	`jnl`	Stochastic momentum methods for non-convex learning without bounded assumptions. Neural Networks Yuqing Liang, Jinlan Liu, Dongpo Xu
2023	J	`jnl`	UAdam: Unified Adam-Type Algorithmic Framework for Non-Convex Stochastic Optimization. CoRR Yiming Jiang, Jinlan Liu, Dongpo Xu, Danilo P. Mandic
2022	J	`jnl`	Convergence analysis of AdaBound with relaxed bound functions for non-convex optimization. Neural Networks Jinlan Liu, Jun Kong, Dongpo Xu, Miao Qi, Yinghua Lu
2022	J	`jnl`	Last-iterate convergence analysis of stochastic momentum methods for neural networks. CoRR Dongpo Xu, Jinlan Liu, Yinghua Lu, Jun Kong, Danilo P. Mandic
2022	J	`jnl`	SGD-rα: A real-time α-suffix averaging method for SGD with biased gradient estimates. Neurocomputing Jianqi Luo, Jinlan Liu, Dongpo Xu, Huisheng Zhang
2021	J	`jnl`	Decreasing scaling transition from adaptive gradient descent to stochastic gradient descent. CoRR Kun Zeng, Jinlan Liu, Zhixia Jiang, Dongpo Xu
2021	J	`jnl`	Scaling transition from momentum stochastic gradient descent to plain stochastic gradient descent. CoRR Kun Zeng, Jinlan Liu, Zhixia Jiang, Dongpo Xu
2020	J	`jnl`	Split-Bregman Algorithm with Attenuation Correction for L-Shell Polychromatic X-ray Fluorescence Computed Tomography. J. Medical Imaging Health Informatics Long Liu, Bo Ma, Xiaowei Liu, Jinlan Liu, Ning Ding
2009	—	`conf`	Hybrid Memetic Algorithm for Uniting Classes of University Timetabling Problem. CIS (2) Zan Wang, Jinlan Liu
2009	—	`conf`	Self-fertilization based genetic algorithm for university timetabling problem. GEC Summit Zan Wang, Jinlan Liu, Xue Yu
2007	—	`conf`	A Hybrid Immune Genetic Algorithm Approach to Optimize the Integrated Forward/Reverse Logistics Network for 3PLs. ICNC (3) Jinlan Liu, Ni Jian
2007	—	`conf`	A New Approach to Forecast Crude Oil Price Based on Fuzzy Neural Network. FSKD (3) Jinlan Liu, Yin Bai, Bin Li
2007	—	`conf`	Fuzzy Clustering Graph for Graded-Evaluation of Hydrocarbon Reserves Value. FSKD (4) Jinlan Liu, Yuan Li, Xiaojun Zhou
2007	—	`conf`	Fuzzy Influence Diagrams: An Approach to Customer Satisfaction Measurement. FSKD (4) Na An, Jinlan Liu, Yin Bai
2007	—	`conf`	The MCMC Approach for Solving the Pareto/NBD Model and Possible Extensions. ICNC (2) Shao-Hui Ma, Jinlan Liu
2007	Misc	`conf`	Using DEA and Grey Markovian Model to Measure the Goal Cost of Petroleum Enterprise. International Conference on Computational Science (3) Jinlan Liu, Meng-dong Wang, Yin Bai
2006	—	`conf`	Risk Analysis for Oil and Gas Exploration Project. CIMCA/IAWTIC Jinlan Liu, Yin Bai, Ying Yu