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Jinlan Liu
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2020 – today
- 2024
- [j9]Mubai Li, Zhenxin Zhang, Siyun Chen, Liqiang Zhang, Zhihua Xu, Xiaoxu Ren, Jinlan Liu, Peng Sun:
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 132: 104041 (2024) - [j8]Yuqing Liang, Yang Yang, Jinlan Liu, Dongpo Xu
:
Shuffling-type gradient method with bandwidth-based step sizes for finite-sum optimization. Neural Networks 179: 106514 (2024) - [j7]Qiankun Diao
An Iterative Algorithm for Quaternion Eigenvalue Problems in Signal Processing. IEEE Signal Process. Lett. 31: 2505-2509 (2024) - [j6]Yuqing Liang
mPage: Probabilistic Gradient Estimator With Momentum for Non-Convex Optimization. IEEE Trans. Signal Process. 72: 1375-1386 (2024) - [c8]Hongliang Sun, Feifei Wang, Meng Wang, Jinlan Liu, Qiao Guan:
Optimization Algorithm for Emission Reduction Schemes Based on Carbon Footprint Prediction. ICSS 2024: 174-187 - [c7]Hongliang Sun, Jinlan Liu, Can Wang, Dianbo Sui, Zhiying Tu, Xiaofei Xu:
Learning Dynamic Knowledge Graph Embedding in Evolving Service Ecosystems via Meta-Learning. ICWS 2024: 601-610 - 2023
- [j5]Jinlan Liu
Last-iterate convergence analysis of stochastic momentum methods for neural networks. Neurocomputing 527: 27-35 (2023) - [j4]Yuqing Liang, Jinlan Liu, Dongpo Xu
Stochastic momentum methods for non-convex learning without bounded assumptions. Neural Networks 165: 830-845 (2023) - [i5]Yiming Jiang, Jinlan Liu, Dongpo Xu, Danilo P. Mandic:
UAdam: Unified Adam-Type Algorithmic Framework for Non-Convex Stochastic Optimization. CoRR abs/2305.05675 (2023) - [i4]Meixuan He, Yuqing Liang, Jinlan Liu, Dongpo Xu:
Convergence of Adam for Non-convex Objectives: Relaxed Hyperparameters and Non-ergodic Case. CoRR abs/2307.11782 (2023) - 2022
- [j3]Jianqi Luo, Jinlan Liu, Dongpo Xu
SGD-rα: A real-time α-suffix averaging method for SGD with biased gradient estimates. Neurocomputing 487: 1-8 (2022) - [j2]Jinlan Liu
Convergence analysis of AdaBound with relaxed bound functions for non-convex optimization. Neural Networks 145: 300-307 (2022) - [i3]Dongpo Xu
Last-iterate convergence analysis of stochastic momentum methods for neural networks. CoRR abs/2205.14811 (2022) - 2021
- [i2]Kun Zeng, Jinlan Liu, Zhixia Jiang, Dongpo Xu:
Decreasing scaling transition from adaptive gradient descent to stochastic gradient descent. CoRR abs/2106.06749 (2021) - [i1]Kun Zeng, Jinlan Liu, Zhixia Jiang, Dongpo Xu:
Scaling transition from momentum stochastic gradient descent to plain stochastic gradient descent. CoRR abs/2106.06753 (2021) - 2020
- [j1]Long Liu, Bo Ma, Xiaowei Liu, Jinlan Liu, Ning Ding:
Split-Bregman Algorithm with Attenuation Correction for L-Shell Polychromatic X-ray Fluorescence Computed Tomography. J. Medical Imaging Health Informatics 10(3): 572-578 (2020)
2000 – 2009
- 2007
- [c6]Jinlan Liu, Yin Bai, Bin Li:
A New Approach to Forecast Crude Oil Price Based on Fuzzy Neural Network. FSKD (3) 2007: 273-277 - [c5]Jinlan Liu, Yuan Li, Xiaojun Zhou:
Fuzzy Clustering Graph for Graded-Evaluation of Hydrocarbon Reserves Value. FSKD (4) 2007: 488-492 - [c4]Na An, Jinlan Liu, Yin Bai:
Fuzzy Influence Diagrams: An Approach to Customer Satisfaction Measurement. FSKD (4) 2007: 493-497 - [c3]Jinlan Liu, Meng-dong Wang, Yin Bai:
Using DEA and Grey Markovian Model to Measure the Goal Cost of Petroleum Enterprise. International Conference on Computational Science (3) 2007: 1008-1011 - [c2]Jinlan Liu, Ni Jian:
A Hybrid Immune Genetic Algorithm Approach to Optimize the Integrated Forward/Reverse Logistics Network for 3PLs. ICNC (3) 2007: 609-613 - 2006
- [c1]Jinlan Liu, Yin Bai, Ying Yu:
Risk Analysis for Oil and Gas Exploration Project. CIMCA/IAWTIC 2006: 214
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