Jinglu Hu

发表

Distributed multi-relational data mining based on genetic algorithm

Kotaro Hirasawa, Jinglu Hu, Gengfeng Wu, 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

Class Association Rule Mining with Chi-Squared Test Using Genetic Network Programming

Kotaro Hirasawa, Kaoru Shimada, Jinglu Hu, 2006, 2006 IEEE International Conference on Systems, Man and Cybernetics.

Comparison between Genetic Network Programming (GNP) and Genetic Programming (GP)

Kotaro Hirasawa, Junichi Murata, Jinglu Hu, 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

A Quasi-ARMAX approach to modelling of non-linear systems

K. Hirasawa, K. Kumamaru, Jinglu Hu, 2001 .

Stability analysis of a DC motor system using universal learning networks

Kotaro Hirasawa, Jinglu Hu, Ahmed Hussein, 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

Generalization Ability of Dynamic Systems by Using Second Order Derivatives of Universal Learning Network

J. Murata, K. Hirasawa, Jinglu Hu, 1999 .

Robust Control for Universal Learning Network Considering Fuzzy Criterion and Second Order Derivatives

Kotaro Hirasawa, Masanao Ohbayashi, Junichi Murata, 1998 .

Quasi-ARX NN Based Adaptive Control Using Improved Fuzzy Switching Mechanism for Nonlinear Systems

Jinglu Hu, Imam Sutrisno, Jinglu Hu, 2014 .

Feature subset selection: a correlation‐based SVM filter approach

Jinglu Hu, Boyang Li, Jinglu Hu, 2011 .

A Homotopy Approach to Identification of ARMAX Systems

K. Hirasawa, Jinglu Hu, 1999 .

An Updated Functional Annotation of Protein-Coding Genes in the Cucumber Genome

Erli Pang, Kui Lin, Jinglu Hu, 2018, Front. Plant Sci..

Feature selection for Human resource selection based on Affinity Propagation and SVM sensitivity analysis

Jinglu Hu, Boyang Li, Qiangwei Wang, 2009, 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC).

Multi‐SVM classifier system with piecewise interpolation

Jinglu Hu, Boyang Li, Jinglu Hu, 2013 .

Nonlinear Control Method based on Impulse Response of Universal Learning Networks

J. Murata, K. Hirasawa, Jinglu Hu, 2002 .

The International Congress for global Science and Technology

Jinglu Hu, Qieshi Zhang, M. Asif, 2009 .

A genetic network programming based method to mine generalized association rules with ontology

Shingo Mabu, Kotaro Hirasawa, Kaoru Shimada, 2008, SICE Annual Conference 2007.

The 2012 International Joint Conference on Neural Networks (IJCNN), Brisbane, Australia, June 10-15, 2012

Aranildo R. Lima, Wei Wang, Brendan McCane, 2012, IJCNN.

Stability analysis of nonlinear systems using high order derivatives of universal learning networks

J. Murata, K. Hirasawa, Jinglu Hu, 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

A new cooperative approach to discrete particle swarm optimization

Jinglu Hu, K. Hirasawa, Yiheng Xu, 2007, SICE Annual Conference 2007.

RasID - Random Search for Neural Network Training

Kotaro Hirasawa, Junichi Murata, Jinglu Hu, 1998, J. Adv. Comput. Intell. Intell. Informatics.

Learning using surface fitting (LeSurf)

K. Hirasawa, Jinglu Hu, M. Hashimoto, 2002, Proceedings of the 41st SICE Annual Conference. SICE 2002..

Implementation of Lyapunov learning algorithm for fuzzy switching adaptive controller modeled under Quasi-ARX Neural Network

Jinglu Hu, Imam Sutrisno, Mohammad Abu Jami'in, 2013, Proceedings of 2013 2nd International Conference on Measurement, Information and Control.

Propabilistic Universal Learning Network Theory

Kotaro Hirasawa, Masanao Ohbayashi, Junichi Murata, 1998 .

Context-Based Segmentation of Renal Corpuscle from Microscope Renal Biopsy Image Sequence

Jinglu Hu, Jun Zhang, Jinglu Hu, 2015, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

Transfer Learning Based Motor Imagery of Stroke Patients for Brain-Computer Interface

Jian Lian, Yuanjie Zheng, Fangzhou Xu, 2020 .

Surface Reconstruction of Renal Corpuscle from Microscope Renal Biopsy Image Sequence

Jun Zhang, Jinglu Hu, Jinglu Hu, 2016, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

Color Quantization Based on Hierarchical Frequency Sensitive Competitive Learning

Jun Zhang, Jinglu Hu, Jinglu Hu, 2010, J. Adv. Comput. Intell. Intell. Informatics.

Use of pseudo measurement to real-time target tracking

J. Murata, Jinglu Hu, C. Jin, 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

Adaptive random search with intensification and diversification combined with genetic algorithm

Shingo Mabu, Kotaro Hirasawa, Jinglu Hu, 2005, 2005 IEEE Congress on Evolutionary Computation.

Genetic Network Programming and Its Application to the Multiagent System

Kotaro Hirasawa, Junichi Murata, Jinglu Hu, 2002 .

Game-theoretic modeling of power supply chain coordination under demand variation in China: A case study of Guangdong Province

Jinglu Hu, Weiming Chen, Xiaoge Tian, 2022, Energy.

Attentive Relation Network for Object based Video Games

Jinglu Hu, Jia Luo, Hangyu Deng, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

Overlapped Multi-Neural-Network and Its Training Algorithm

Kotaro Hirasawa, Jinglu Hu, Qingyu Xiong, 2001 .

Learning a Latent Space with Triplet Network for Few-Shot Image Classification

Jinglu Hu, Jiaying Wu, 2022, 2022 26th International Conference on Pattern Recognition (ICPR).

An improved adaptive switching control based on quasi-ARX neural network for nonlinear systems

Jinglu Hu, I. Sutrisno, Chi Che, 2014, Artificial Life and Robotics.

Solving deceptive problems using a genetic algorithm with reserve selection

Kotaro Hirasawa, Jinglu Hu, Yang Chen, 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

A Convolutional Auto-Encoder Method for Anomaly Detection on System Logs

Yu Cui, Gehao Sheng, Jinglu Hu, 2018, 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Propagation and control of stochastic signals through universal learning networks

Shingo Mabu, Kotaro Hirasawa, Jinglu Hu, 2006, Neural Networks.

Improvement of generalization ability for identifying dynamical systems by using universal learning networks

Kotaro Hirasawa, Sung-Ho Kim, Junichi Murata, 2001, Neural Networks.

Identification of nonlinear dynamic systems by using probabilistic universal learning networks

Kotaro Hirasawa, Junichi Murata, Jinglu Hu, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

Accurate Reconstruction for DNA Sequencing by Hybridization Based on a Constructive Heuristic

Jinglu Hu, Yang Chen, Jinglu Hu, 2011, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

eSBH: An Accurate Constructive Heuristic Algorithm for DNA Sequencing by Hybridization

Jinglu Hu, Yang Chen, Jinglu Hu, 2010, 2010 IEEE International Conference on BioInformatics and BioEngineering.

An Improved Discrete Particle Swarm Optimization Based on Cooperative Swarms

Jinglu Hu, Yiheng Xu, Qiangwei Wang, 2008, 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

Robust Fault Detection Using Index of Kullback Discrimination Information

Torsten Söderström, Jinglu Hu, Kousuke Kumamaru, 1996 .

A Laplacian SVM Based Semi‐Supervised Classification Using Multi‐Local Linear Model

Jinglu Hu, Huilin Zhu, Yanling Tian, 2021, IEEJ Transactions on Electrical and Electronic Engineering.

A Semi-supervised Classification Using Gated Linear Model

Weite Li, Jinglu Hu, Yanni Ren, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

A coarse‐to‐fine two‐step method for semisupervised classification using quasi‐linear Laplacian SVM

Weite Li, Jinglu Hu, Bo Zhou, 2018, IEEJ Transactions on Electrical and Electronic Engineering.

A Transductive SVM with quasi-linear kernel based on cluster assumption for semi-supervised classification

Jinglu Hu, Bo Zhou, Chao Dong, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

A Transductive Support Vector Machine with adjustable quasi-linear kernel for semi-supervised data classification

Jinglu Hu, Bo Zhou, Benhui Chen, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

A new control method of nonlinear systems based on impulse responses of universal learning networks

Kotaro Hirasawa, Junichi Murata, Jinglu Hu, 1998, IEEE Trans. Syst. Man Cybern. Part B.

Lotka-Volterra Systems under Consideration of Fuzzy Symbiosis and Learning

Kotaro Hirasawa, Junichi Murata, Jinglu Hu, 1999 .

A novel registration method based on coevolutionary strategy

Jun Zhang, Jinglu Hu, Jinglu Hu, 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

Image Segmentation Based on 2D Otsu Method with Histogram Analysis

Jun Zhang, Jinglu Hu, Jinglu Hu, 2008, 2008 International Conference on Computer Science and Software Engineering.

Differential Evolution for Rule Extraction and Its application in Recognizing Oil Reservoir

Jinglu Hu, Jinling Li, Haixiang Guo, 2013, J. Digit. Inf. Manag..

GARS: an improved genetic algorithm with reserve selection for global optimization

Kotaro Hirasawa, Jinglu Hu, Yang Chen, 2007, GECCO '07.

Vulnerability Dataset Construction Methods Applied To Vulnerability Detection: A Survey

Jinglu Hu, Qiuling Yue, Hongyu Sun, 2022, 2022 52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W).

Genetic Symbiosis Algorithm for Multiobjective Optimization Problems

Kotaro Hirasawa, Junichi Murata, Jinglu Hu, 2001 .

Increasing Robustness Of Genetic Algorithm

Kotaro Hirasawa, Junichi Murata, Jinglu Hu, 2002, GECCO.

Genetic network programming with sarsa learning and its application to creating stock trading rules

Shingo Mabu, Kotaro Hirasawa, Jinglu Hu, 2007, 2007 IEEE Congress on Evolutionary Computation.

A study of applying Genetic Network Programming with Reinforcement Learning to Elevator Group Supervisory Control System

Shingo Mabu, Kotaro Hirasawa, Jinglu Hu, 2006, 2006 IEEE International Conference on Evolutionary Computation.

Elevator group supervisory control system using genetic network programming with reinforcement learning

Kotaro Hirasawa, Jinglu Hu, Jin Zhou, 2005, 2005 IEEE Congress on Evolutionary Computation.

Adaptive random search with intensification and diversification combined with genetic algorithm

Kotaro Hirasawa, Jinglu Hu, DongKyu Sohn, 2005, 2005 IEEE Congress on Evolutionary Computation.

Computing of the contribution rate of scientific and technological progress to economic growth in Chinese regions

Jinglu Hu, Haixiang Guo, Han Sun, 2012, Expert Syst. Appl..

Acceleration of a CUDA-Based Hybrid Genetic Algorithm and its Application to a Flexible Flow Shop Scheduling Problem

Jinglu Hu, Jia Luo, Didier El Baz, 2018, 2018 19th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD).

Improving Image Captioning Evaluation by Considering Inter References Variance

Jinglu Hu, Hangyu Deng, Yanzhi Yi, 2020, ACL.

A Graph-Based Evolutionary Algorithm: Genetic Network Programming (GNP) and Its Extension Using Reinforcement Learning

Shingo Mabu, Kotaro Hirasawa, Jinglu Hu, 2007, Evolutionary Computation.

Comparing some graph crossover in genetic network programming

Kotaro Hirasawa, Junichi Murata, Jinglu Hu, 2002, Proceedings of the 41st SICE Annual Conference. SICE 2002..

Financial time series prediction using a support vector regression network

Kotaro Hirasawa, Jinglu Hu, Boyang Li, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

A Hybrid EDA for Protein Folding Based on HP Model

Jinglu Hu, Benhui Chen, Jinglu Hu, 2010 .

Protein Structure Prediction Based on HP Model Using an Improved Hybrid EDA

Jinglu Hu, Benhui Chen, Jinglu Hu, 2010 .

An improved backtracking method for EDAs based protein folding

Jinglu Hu, Benhui Chen, Jinglu Hu, 2009, 2009 ICCAS-SICE.

A novel EDAs based method for HP model protein folding

Long Li, Jinglu Hu, Benhui Chen, 2009, 2009 IEEE Congress on Evolutionary Computation.

Universal learning network and its application to chaos control

Kotaro Hirasawa, Xiaofeng Wang, Junichi Murata, 2000, Neural Networks.

Chaos control on universal learning networks

Kotaro Hirasawa, Junichi Murata, Jinglu Hu, 2000, IEEE Trans. Syst. Man Cybern. Part C.

Chaos control using maximum Lyapunov number of universal learning network

Kotaro Hirasawa, Xiaofeng Wang, Junichi Murata, 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

Solving the dynamic energy aware job shop scheduling problem with the heterogeneous parallel genetic algorithm

Jinglu Hu, Didier El Baz, Rui Xue, 2020, Future Gener. Comput. Syst..

Double-deck Elevator Group Supervisory Control System using Genetic Network Programming with Ant Colony Optimization

Shingo Mabu, Kotaro Hirasawa, Jinglu Hu, 2007, 2007 IEEE Congress on Evolutionary Computation.

Elevator group control system using genetic network programming with ACO considering transitions

Jinglu Hu, Jin Zhou, Lu Yu, 2007, SICE Annual Conference 2007.

Genetic Network Programming with Reinforcement Learning Using Sarsa Algorithm

Shingo Mabu, Kotaro Hirasawa, Jinglu Hu, 2006, 2006 IEEE International Conference on Evolutionary Computation.

Genetic Network Programming with Reinforcement Learning and Its Performance Evaluation

Shingo Mabu, Kotaro Hirasawa, Jinglu Hu, 2004, GECCO.

Genetic network programming with learning and evolution for adapting to dynamical environments

Shingo Mabu, Kotaro Hirasawa, Jinglu Hu, 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

Online Learning of Genetic Network Programming

Shingo Mabu, Kotaro Hirasawa, Junichi Murata, 2002 .

Genetic network programming - application to intelligent agents

Jinglu Hu, Hironobu Katagiri, Kotaro Hirasama, 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

Neural‐augmented two‐stage Monte Carlo tree search with over‐sampling for protein folding in HP Model

Jinglu Hu, Yanling Tian, Hangyu Deng, 2022, IEEJ Transactions on Electrical and Electronic Engineering.

Quasi‐linear SVM classifier with segmented local offsets for imbalanced data classification

Feng Zheng, Weite Li, Jinglu Hu, 2018, IEEJ Transactions on Electrical and Electronic Engineering.

A Segmented Local Offset Method for Imbalanced Data Classification Using Quasi-Linear Support Vector Machine

Jinglu Hu, Xin Yuan, Weite Li, 2018, 2018 24th International Conference on Pattern Recognition (ICPR).

Composite kernel based SVM for hierarchical multi-label gene function classification

Jinglu Hu, Benhui Chen, Lihua Duan, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

Hierarchical multi‐label classification based on over‐sampling and hierarchy constraint for gene function prediction

Benhui Chen, Jinglu Hu, Jinglu Hu, 2012 .

An SVM-based approach for stock market trend prediction

Jinglu Hu, Haixiang Guo, Yuling Lin, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

A study of evolutionary multiagent models based on symbiosis

Kotaro Hirasawa, Jinglu Hu, Toru Eguchi, 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

Oversampling the minority class in a multi‐linear feature space for imbalanced data classification

Weite Li, Jinglu Hu, Peifeng Liang, 2018, IEEJ Transactions on Electrical and Electronic Engineering.

A new segmented oversampling method for imbalanced data classification using quasi‐linear SVM

Bo Zhou, Jinglu Hu, Weite Li, 2017 .

A novel frequency band selection method for Common Spatial Pattern in Motor Imagery based Brain Computer Interface

Jinglu Hu, Gengfeng Wu, Gufei Sun, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Enhancing the generalization ability of neural networks through controlling the hidden layers

Shingo Mabu, Kotaro Hirasawa, Kaoru Shimada, 2009, Appl. Soft Comput..

A Hybrid Robust Identification Using Genetic Algorithm and Gradient Method

Jinglu Hu, Kousuke Kumamaru, Katsuhiro Inoue, 1996 .

A two‐step scheme for polynomial NARX model identification based on MOEA with prescreening process

Yu Cheng, Lan Wang, Jinglu Hu, 2011 .

Optimizing reserve size in genetic algorithms with reserve selection using reinforcement learning

Jinglu Hu, K. Hirasawa, Yang Chen, 2007, SICE Annual Conference 2007.

Constructing a PPI Network Based on Deep Transfer Learning for Protein Complex Detection

Jinglu Hu, Hangyu Deng, Xin Yuan, 2021, IEEJ Transactions on Electrical and Electronic Engineering.

Glomerulus Extraction by Optimizing the Fitting Curve

Jun Zhang, Jinglu Hu, Jinglu Hu, 2008, 2008 International Symposium on Computational Intelligence and Design.

Improving SVM based multi-label classification by using label relationship

Jinglu Hu, Bo Zhou, Di Fu, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Improving multi-label classification performance by label constraints

Jinglu Hu, Benhui Chen, Lihua Duan, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

Combining binary-SVM and pairwise label constraints for multi-label classification

Jinglu Hu, Benhui Chen, Weifeng Gu, 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.

Hierarchical Multi-label Classification incorporating prior information for gene function prediction

Jinglu Hu, Benhui Chen, Jinglu Hu, 2010, 2010 10th International Conference on Intelligent Systems Design and Applications.

An improved multi-label classification method and its application to functional genomics

Jinglu Hu, Benhui Chen, Weifeng Gu, 2010, Int. J. Comput. Biol. Drug Des..

An improved multi-label classification based on label ranking and delicate boundary SVM

Jinglu Hu, Benhui Chen, Weifeng Gu, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Nonlinear system identification based on SVR with quasi-linear kernel

Yu Cheng, Jinglu Hu, Y. Cheng, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

A two-step method for nonlinear polynomial model identification based on evolutionary optimization

Yu Cheng, Jinglu Hu, Lan Wang, 2009, 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC).

Neural Network Based Prediction Model for Control of Nonlinear Systems

Kotaro Hirasawa, Jinglu Hu, K. Hirasawa, 2003 .

Quasi-ARX wavelet network for SVR based nonlinear system identification

Yu Cheng, Lan Wang, Jinglu Hu, 2011 .

A Method for Applying Neural Networks to Control of Nonlinear Systems

Kotaro Hirasawa, Jinglu Hu, K. Hirasawa, 2004 .

A QUASI-ARX MODEL INCORPORATING NEURAL NETWORK FOR CONTROL OF NONLINEAR SYSTEMS

Kotaro Hirasawa, Jinglu Hu, Kousuke Kumamaru, 2002 .

A Hybrid Model for Nonlinear Regression with Missing Data Using Quasilinear Kernel

Jinglu Hu, Yanling Tian, Huilin Zhu, 2020, IEEJ Transactions on Electrical and Electronic Engineering.

Glomeruli extraction by canny operator with a feedback strategy

Jinglu Hu, Hong Zhu, Jun Zhang, 2010, International Conference on Digital Image Processing.

Glomerulus extraction by using genetic algorithm for edge patching

Jinglu Hu, Jingqiao Zhang, Jiaxin Ma, 2009, 2009 IEEE Congress on Evolutionary Computation.

A Quasi-linear Approach for Microarray Missing Value Imputation

Yu Cheng, Jinglu Hu, Lan Wang, 2011, ICONIP.

Identification of Quasi-ARX neurofuzzy model by using SVR-based approach with input selection

Jing Zeng, Jinglu Hu, Lan Wang, 2011, 2011 IEEE International Conference on Systems, Man, and Cybernetics.

COVID-19 infodemic on Chinese social media: A 4P framework, selective review and research directions

Jinglu Hu, Rui Xue, Jia Luo, 2020 .

Genetic network programming with class association rule acquisition mechanisms from incomplete database

Jinglu Hu, K. Hirasawa, K. Shimada, 2007, SICE Annual Conference 2007.

Mining association rules from databases with continuous attributes using genetic network programming

Shingo Mabu, Kotaro Hirasawa, Eloy Gonzales, 2007, 2007 IEEE Congress on Evolutionary Computation.

Association Rule Mining with Chi-Squared Test Using Alternate Genetic Network Programming

Kotaro Hirasawa, Kaoru Shimada, Jinglu Hu, 2006, ICDM.

Genetic Network Programming with Acquisition Mechanisms of Association Rules in Dense Database

Kotaro Hirasawa, Kaoru Shimada, Jinglu Hu, 2005, International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06).

Similitude Attentive Relation Network for Click-Through Rate Prediction

Yulong Wang, Jinglu Hu, Hangyu Deng, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

A Metric Learning Method for Improving Neural Network Based Kernel Learning for SVM

Jinglu Hu, Peifeng Liang, Xueqin Yao, 2018, 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

A geometry‐based two‐step method for nonlinear classification using quasi‐linear support vector machine

Jinglu Hu, Weite Li, Benhui Chen, 2017 .

Non-local information for a mixture of multiple linear classifiers

Jinglu Hu, Xin Yuan, Weite Li, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

A mixture of multiple linear classifiers with sample weight and manifold regularization

Jinglu Hu, Weite Li, Bo Zhou, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

A kernel level composition of multiple local classifiers for nonlinear classification

Jinglu Hu, Weite Li, Bo Zhou, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

Geometric approach of quasi-linear kernel composition for support vector machine

Jinglu Hu, Weite Li, Jinglu Hu, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Support vector machine with SOM-based quasi-linear kernel for nonlinear classification

Yong Fu, Jinglu Hu, Yuling Lin, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

Quasi-Linear Support Vector Machine for Nonlinear Classification

Jinglu Hu, Bo Zhou, Benhui Chen, 2014, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

Local linear multi-SVM method for gene function classification

Jinglu Hu, Benhui Chen, Feiran Sun, 2010, 2010 Second World Congress on Nature and Biologically Inspired Computing (NaBIC).

A Deep Learning Approach Based on Stacked Denoising Autoencoders for Protein Function Prediction

Jinglu Hu, Lester James V. Miranda, Jinglu Hu, 2018, 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC).

Quick response data mining model using genetic algorithm

Jinglu Hu, Gengfeng Wu, K. Hirasawa, 2008, 2008 SICE Annual Conference.

A fast SVM training method for very large datasets

Jinglu Hu, Boyang Li, Qiangwei Wang, 2009, 2009 International Joint Conference on Neural Networks.

The comparison of alternative splicing among the multiple tissues in cucumber

Erli Pang, Kui Lin, Jinglu Hu, 2018, BMC Plant Biology.

Understanding Pedestrian Trajectory Prediction from the Planning Perspective

Jinglu Hu, Dongcheng Li, 2023, IEEJ Transactions on Electrical and Electronic Engineering.

Adaptive epsilon non-dominated sorting multi-objective evolutionary optimization and its application in shortest path problem

Y. Cheng, Jinglu Hu, Yongjie Jin, 2009, 2009 ICCAS-SICE.

A Semi‐supervised Classification Method of Parasites Using Contrastive Learning

Jinglu Hu, Huilin Zhu, Yanling Tian, 2021, IEEJ Transactions on Electrical and Electronic Engineering.

A new random search method for neural network learning-RasID

Masanao Ohbayashi, Jinglu Hu, Kotaro Hirasawa, 1998, 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227).

A fast sequence assembly method based on compressed data structures

Jinglu Hu, Peifeng Liang, Kui Lin, 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

The comparison of alternative splicing among the multiple tissues in cucumber

Erli Pang, Kui Lin, Jinglu Hu, 2018, BMC Plant Biology.

Comparative study on economic contribution rate of education of China and foreign countries based on soft computing method

Jinglu Hu, Haixiang Guo, Han Sun, 2012, Appl. Soft Comput..

A multilayer gated bilinear classifier: From optimizing a deep rectified network to a support vector machine

Jinglu Hu, Weite Li, Jinglu Hu, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Stacked residual recurrent neural network with word weight for text classification

Anping Song, Jinglu Hu, Wei Cao, 2017 .

Determination of the appropriate node function of NNs by using the cascade-correlation algorithms

Kotaro Hirasawa, Junichi Murata, Jinglu Hu, 2000, 2000 26th Annual Conference of the IEEE Industrial Electronics Society. IECON 2000. 2000 IEEE International Conference on Industrial Electronics, Control and Instrumentation. 21st Century Technologies.

Redefining prior feature space via finetuning a triplet network for few-shot learning

Jinglu Hu, Jiaying Wu, 2022, IET Comput. Vis..

A New Minimax Control Method for Nonlinear Systems Using Universal Learning Networks

Kotaro Hirasawa, Junichi Murata, Jinglu Hu, 2001 .

Min-max control of nonlinear systems using universal learning networks

Kotaro Hirasawa, Junichi Murata, Jinglu Hu, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Air Quality Forecasting Using SVR with Quasi-Linear Kernel

Jinglu Hu, Huilin Zhu, Jinglu Hu, 2019, 2019 International Conference on Computer, Information and Telecommunication Systems (CITS).

Nonlinear System Identification Using Quasi-ARX RBFN Models with a Parameter-Classified Scheme

Yu Cheng, Jinglu Hu, Lan Wang, 2017, Complex..

Distance metric learning with eigenvalue fine tuning

Ya Zhang, Jinglu Hu, Wenquan Wang, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Fast Support Vector Data Description training using edge detection on large datasets

Jinglu Hu, Bo Zhou, Chenlong Hu, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

Poisson approach to clustering analysis of regulatory sequences

Huiru Zheng, Haiying Wang, Jinglu Hu, 2008, Int. J. Comput. Biol. Drug Des..

Cluster Analysis of Regulatory Sequences with a Log Likelihood Ratio Statistics-based Similarity Measure

Huiru Zheng, Haiying Wang, Jinglu Hu, 2007, 2007 IEEE 7th International Symposium on BioInformatics and BioEngineering.

A quasi-linear SVM combined with assembled SMOTE for imbalanced data classification

Jinglu Hu, Cheng Yang, Bo Zhou, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

Elevator group supervisory control systems using genetic network programming

Shingo Mabu, Kotaro Hirasawa, Jinglu Hu, 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

Online Learning of Genetic Network Programming and its Application to Prisoner's Dilemma Game

Shingo Mabu, Kotaro Hirasawa, Junichi Murata, 2003 .

Learning of Genetic Network Programming ( GNP )

J. Murata, K. Hirasawa, Jinglu Hu, 2002 .

An efficient identification scheme for a nonlinear polynomial NARX model

Yu Cheng, Lan Wang, Jinglu Hu, 2011, Artificial Life and Robotics.

Stock trading rules using genetic network programming with actor-critic

Shingo Mabu, Kotaro Hirasawa, Jinglu Hu, 2007, 2007 IEEE Congress on Evolutionary Computation.

Buying and selling stocks of multi brands using genetic network programming with control nodes

Jinglu Hu, S. Mabu, K. Hirasawa, 2007, SICE Annual Conference 2007.

Elevator Group Supervisory Control System Using Genetic Network Programming with Macro Nodes and Reinforcement Learning

Shingo Mabu, Kotaro Hirasawa, Jinglu Hu, 2007 .

Trading Rules on the Stock Markets Using Genetic Network Programming with Importance Index

Kotaro Hirasawa, Jinglu Hu, Yoshihiro Izumi, 2006 .

Genetic Network Programming with Evolution and Learning and Its Application to the Tileworld Problem

Shingo Mabu, Kotaro Hirasawa, Jinglu Hu, 2004 .

Online learning of genetic network programming (GNP)

Shingo Mabu, Kotaro Hirasawa, Junichi Murata, 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

Hybrid Universal Learning Networks

Kotaro Hirasawa, Junichi Murata, Jinglu Hu, 2003 .

Relation‐Level User Behavior Modeling for Click‐Through Rate Prediction

Jinglu Hu, Jia Luo, Yanling Tian, 2021, IEEJ Transactions on Electrical and Electronic Engineering.

A Quasi-ARX Neural Network with Switching Mechanism to Adaptive Control of Nonlinear Systems

Yu Cheng, Lan Wang, Jinglu Hu, 2010 .

A Learning Method for Dynamics of Multi-Agent System with Mutual Interaction Based on Fuzzy Inference

Kotaro Hirasawa, Jinglu Hu, Junichiro Misawa, 1999 .

Generating High Coherence Monophonic Music Using Monte-Carlo Tree Search

Jinglu Hu, Hangyu Deng, Xin Yuan, 2023, IEEE Transactions on Multimedia.

A Winner‐Take‐All Autoencoder Based Pieceswise Linear Model for Nonlinear Regression with Missing Data

Jinglu Hu, Huilin Zhu, Yanling Tian, 2021, IEEJ Transactions on Electrical and Electronic Engineering.

One‐class classification using a support vector machine with a quasi‐linear kernel

Jinglu Hu, Hao Tian, Weite Li, 2018, IEEJ Transactions on Electrical and Electronic Engineering.

One-Class Classification Using Quasi-Linear Support Vector Machine

Yudong Wang, Jinglu Hu, Weite Li, 2018, 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

A Semi-Supervised Classification Method of Apicomplexan Parasites and Host Cell using Contrastive Learning Strategy

Jinglu Hu, Hangyu Deng, Yanni Ren, 2021, 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC).