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ORCIDDingli Yu
Ding-Li Yu – D. L. Yu
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- affiliation: Liverpool John Moores University, Liverpool, UK
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2020 – today
- 2024
[j45]Hongrui Li, Shuangxin Wang, Jiading Jiang, Chuiyi Deng
, Junmei Ou, Ziang Zhou, Dingli Yu:
Augmenting the diversity of imbalanced datasets via multi-vector stochastic exploration oversampling. Neurocomputing 583: 127600 (2024)- [c46]Greg Yang, Dingli Yu, Chen Zhu, Soufiane Hayou:
Tensor Programs VI: Feature Learning in Infinite Depth Neural Networks. ICLR 2024 - [c45]Dingli Yu, Simran Kaur, Arushi Gupta, Jonah Brown-Cohen, Anirudh Goyal, Sanjeev Arora:
SKILL-MIX: a Flexible and Expandable Family of Evaluations for AI Models. ICLR 2024 - [i13]Kaifeng Lyu, Haoyu Zhao, Xinran Gu, Dingli Yu, Anirudh Goyal, Sanjeev Arora:
Keeping LLMs Aligned After Fine-tuning: The Crucial Role of Prompt Templates. CoRR abs/2402.18540 (2024) - [i12]Vedant Shah, Dingli Yu, Kaifeng Lyu, Simon Park, Nan Rosemary Ke, Michael Mozer, Yoshua Bengio, Sanjeev Arora, Anirudh Goyal:
AI-Assisted Generation of Difficult Math Questions. CoRR abs/2407.21009 (2024) - [i11]Xindi Wu, Dingli Yu, Yangsibo Huang, Olga Russakovsky, Sanjeev Arora:
ConceptMix: A Compositional Image Generation Benchmark with Controllable Difficulty. CoRR abs/2408.14339 (2024) - [i10]Haoyu Zhao, Simran Kaur, Dingli Yu, Anirudh Goyal, Sanjeev Arora:
Can Models Learn Skill Composition from Examples? CoRR abs/2409.19808 (2024) - 2023
- [c44]Sadhika Malladi, Alexander Wettig, Dingli Yu, Danqi Chen, Sanjeev Arora:
A Kernel-Based View of Language Model Fine-Tuning. ICML 2023: 23610-23641 - [c43]Azizeh Lotfivand, Dingli Yu, Barry Gomm:
State of Charge Estimation Using Unscented Kalman Filter in Electric Vehicles. ICAC 2023: 1-5 - [i9]Greg Yang, Dingli Yu, Chen Zhu, Soufiane Hayou:
Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks. CoRR abs/2310.02244 (2023) - [i8]Dingli Yu, Simran Kaur, Arushi Gupta, Jonah Brown-Cohen, Anirudh Goyal, Sanjeev Arora:
Skill-Mix: a Flexible and Expandable Family of Evaluations for AI models. CoRR abs/2310.17567 (2023) - 2022
- [j44]Kang Ji, Qian Zhang, Zhi Yuan, Hui Cheng, Dingli Yu:
A virtual force interaction scheme for multi-robot environment monitoring. Robotics Auton. Syst. 149: 103967 (2022) - [c42]Azizeh Lotfivand, Dingli Yu, J. Barry Gomm:
State Of Charge estimation using Extended Kalman Filter in Electric Vehicles. ICAC 2022: 1-5 - [c41]Kingsley Madubuike, Cliff Mayhew, Qian Zhang, J. Barry Gomm, Ding-Li Yu:
Fault tolerant control and fault diagnosis of a variable speed pitch angle hydraulic system. ICAC 2022: 1-6 - [c40]Zhiyuan Li, Tianhao Wang, Dingli Yu:
Fast Mixing of Stochastic Gradient Descent with Normalization and Weight Decay. NeurIPS 2022 - [c39]Arushi Gupta, Nikunj Saunshi, Dingli Yu, Kaifeng Lyu, Sanjeev Arora:
New Definitions and Evaluations for Saliency Methods: Staying Intrinsic, Complete and Sound. NeurIPS 2022 - [c38]Kang Ji, Qian Zhang, Dingli Yu:
A Virtual Force-Based Strategy for Multi-robot Target Search. UKCI 2022: 563-575 - [i7]Sadhika Malladi, Alexander Wettig, Dingli Yu, Danqi Chen, Sanjeev Arora:
A Kernel-Based View of Language Model Fine-Tuning. CoRR abs/2210.05643 (2022) - [i6]Arushi Gupta, Nikunj Saunshi, Dingli Yu, Kaifeng Lyu, Sanjeev Arora:
New Definitions and Evaluations for Saliency Methods: Staying Intrinsic, Complete and Sound. CoRR abs/2211.02912 (2022) - 2021
- [j43]Szilárd Novoth, Qian Zhang, Kang Ji, Dingli Yu:
Distributed Formation Control for Multi-Vehicle Systems With Splitting and Merging Capability. IEEE Control. Syst. Lett. 5(1): 355-360 (2021) - [j42]Yulin Mao, Shuangxin Wang, Dingli Yu, Juchao Zhao:
Automatic image detection of multi-type surface defects on wind turbine blades based on cascade deep learning network. Intell. Data Anal. 25(2): 463-482 (2021) - [j41]Yufei Ma, Shuangxin Wang, Dingli Yu, Kaihua Zhu:
Robust visual-inertial odometry with point and line features for blade inspection UAV. Ind. Robot 48(2): 179-188 (2021) - [j40]Yiran Shi, Shoutao Li, Shuangxin Wang, Yujia Zhai, Yantao Tian, Ding-Li Yu:
Pitch angle control with fault diagnosis and tolerance for wind turbine generation systems. J. Syst. Control. Eng. 235(8) (2021) - [j39]Shoutao Li, Yiran Shi, Yujia Zhai, Shuangxin Wang, Yantao Tian, Ding-Li Yu:
Friction fault diagnosis and fault tolerant control for electronic throttles with sliding mode and adaptive RBF estimator. J. Syst. Control. Eng. 235(9) (2021) - [j38]Yiran Shi, Dingli Yu, Hongyan Shi, Yaowu Shi:
A New Concept of Fractional Order Cumulant and It-Based Signal Processing in α and/or Gaussian Noise. IEEE Trans. Inf. Theory 67(3): 1849-1863 (2021) - 2020
- [j37]Yantao Tian, Yanbo Zhao, Yiran Shi, Xuanhao Cao, Ding-Li Yu:
The indirect shared steering control under double loop structure of driver and automation. IEEE CAA J. Autom. Sinica 7(5): 1403-1416 (2020) - [j36]Haiying Qi, Yiran Shi, Shoutao Li, Yantao Tian, Ding-Li Yu, J. B. Gomm:
Fault tolerant control for nonlinear systems using sliding mode and adaptive neural network estimator. Soft Comput. 24(15): 11535-11544 (2020) - [c37]Sanjeev Arora, Simon S. Du, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang, Dingli Yu:
Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks. ICLR 2020 - [c36]Wei Hu, Zhiyuan Li, Dingli Yu:
Simple and Effective Regularization Methods for Training on Noisily Labeled Data with Generalization Guarantee. ICLR 2020 - [c35]Pingzhong Tang, Dingli Yu, Shengyu Zhao:
Characterization of Group-strategyproof Mechanisms for Facility Location in Strictly Convex Space. EC 2020: 133-157
2010 – 2019
- 2019
- [j35]Zifeng Qiu, Shuangxin Wang, Zhaoxi Zeng, Dingli Yu:
Automatic visual defects inspection of wind turbine blades via YOLO-based small object detection approach. J. Electronic Imaging 28(4): 043023 (2019) - [c34]Kang Ji, Qian Zhang, Hui Cheng, Dingli Yu:
A Virtual Force Interaction Scheme for Monitoring Complex Unknown Environments by Autonomous Mobile Robots. ECC 2019: 95-100 - [c33]Kingsley Madubuike, Cliff Mayhew, Qian Zhang, J. Barry Gomm, Ding-Li Yu:
Fault diagnosis for wind turbine systems using a neural network estimator. ICAC 2019: 1-7 - [c32]Kingsley Madubuike, Cliff Mayhew, Qian Zhang, J. Barry Gomm, Ding-Li Yu:
Fault diagnosis for wind turbine systems using unknown input observer. ICAC 2019: 1-6 - [i5]Wei Hu, Zhiyuan Li, Dingli Yu:
Understanding Generalization of Deep Neural Networks Trained with Noisy Labels. CoRR abs/1905.11368 (2019) - [i4]Sanjeev Arora, Simon S. Du, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang, Dingli Yu:
Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks. CoRR abs/1910.01663 (2019) - [i3]Zhiyuan Li, Ruosong Wang, Dingli Yu, Simon S. Du, Wei Hu, Ruslan Salakhutdinov, Sanjeev Arora:
Enhanced Convolutional Neural Tangent Kernels. CoRR abs/1911.00809 (2019) - 2018
- [j34]Lei Gu, D. K. Siong Tok, Ding-Li Yu:
Development of adaptive p-step RBF network model with recursive orthogonal least squares training. Neural Comput. Appl. 29(5): 1445-1454 (2018) - [c31]Ariel D. Procaccia, Rodrigo A. Velez, Dingli Yu:
Fair Rent Division on a Budget. AAAI 2018: 1177-1184 - [c30]Pingzhong Tang, Dingli Yu:
Balanced Outcomes in Wage Bargaining. AAMAS 2018: 2091-2093 - [c29]Haiying Qi, Abdelkarim M. Ertiame, Kingsley Madubuike, Ding-Li Yu, J. Barry Gomm:
Nonlinear Observer Fault Detection for a Multivariable Process Using a Learning Methodology. ICAC 2018: 1-6 - [c28]Haiying Qi, Abdelkarim M. Ertiame, Kingsley Madubuike, Ding-Li Yu, J. Barry Gomm:
Failure Prediction for an Exothermic Semi-batch Reactor via A combined EKF with Statistical Method. ICAC 2018: 1-6 - [i2]Pingzhong Tang, Dingli Yu, Shengyu Zhao:
Group-Strategyproof mechanisms for facility location with Euclidean distance. CoRR abs/1808.06320 (2018) - 2017
- [j33]D. K. Siong Tok, Yiran Shi, Yantao Tian, Ding-Li Yu:
Factorized f-step radial basis function model for model predictive control. Neurocomputing 239: 102-112 (2017) - [j32]Quan Min Zhu, Dingli Yu, Dong-Ya Zhao:
An enhanced linear Kalman filter (EnLKF) algorithm for parameter estimation of nonlinear rational models. Int. J. Syst. Sci. 48(3): 451-461 (2017) - [c27]Mohammed Sufian, Xun Chen, Dingli Yu:
Investigating the capability of precision in robotic grinding. ICAC 2017: 1-6 - [c26]Majid Borairi, Majeed Soufian, D. L. Yu:
Fault detection observer of a pilot plant papermaking machine. ISIE 2017: 1820-1824 - [i1]Wesley Pegden, Ariel D. Procaccia, Dingli Yu:
A partisan districting protocol with provably nonpartisan outcomes. CoRR abs/1710.08781 (2017) - 2016
- [j31]Kumaran Rajarathinam, J. Barry Gomm, Ding-Li Yu, Ahmed Saad Abdelhadi:
PID controller tuning for a multivariable glass furnace process by genetic algorithm. Int. J. Autom. Comput. 13(1): 64-72 (2016) - [c25]Kumaran Rajarathinam, J. Barry Gomm, Dingli Yu, Ahmed Saad Abdelhadi:
Model parameters identification for excess oxygen by Standard Genetic Algorithm. ICAC 2016: 198-203 - 2015
- [j30]Yiran Shi, Ding-Li Yu, Yantao Tian, Yaowu Shi:
Air-fuel ratio prediction and NMPC for SI engines with modified Volterra model and RBF network. Eng. Appl. Artif. Intell. 45: 313-324 (2015) - [j29]D. K. Siong Tok, Dingli Yu, Christian Mathews, Dong-Ya Zhao, Quan Min Zhu:
Adaptive structure radial basis function network model for processes with operating region migration. Neurocomputing 155: 186-193 (2015) - [j28]Shuangxin Wang, Guibin Tian, Dingli Yu, Yijiang Lin:
Dynamic Particle Swarm Optimization with Any Irregular Initial Small-World Topology. Int. J. Swarm Intell. Res. 6(4): 1-23 (2015) - [c24]Kumaran Rajarathianm, J. Barry Gomm, Karl O. Jones, Dingli Yu:
Predetermined time constant approximation method for optimising search space boundary by standard genetic algorithm. CompSysTech 2015: 38-45 - [c23]Kumaran Rajarathinam, J. Barry Gomm, Dingli Yu, Ahmed Saad Abdelhadi:
An improved search space resizing method for model identification by Standard Genetic Algorithm. ICAC 2015: 1-6 - 2014
- [j27]Mahanijah Md Kamal, D. W. Yu, D. L. Yu:
Fault detection and isolation for PEM fuel cell stack with independent RBF model. Eng. Appl. Artif. Intell. 28: 52-63 (2014) - [c22]Kumaran Rajarathinam, J. Barry Gomm, Dingli Yu, Ahmed Saad Abdelhadi:
Decentralised PID control tuning for a multivariable glass furnace by genetic algorithm. ICAC 2014: 14-19 - [c21]Yusheng Liu, Ding-Li Yu:
Robust fault detection for wind turbine systems. ICAC 2014: 38-42 - [c20]Ahmed Saad Abdelhadi, J. Barry Gomm, Dingli Yu, Kumaran Rajarathinam:
Nonlinear system identification and control of a pH process using Local Linear Model Networks strategy. ICAC 2014: 254-259 - 2013
- [j26]Omar Ragb, Dong-Ya Zhao, Dingli Yu, Quan Min Zhu:
Comparison study of different non-linear feed-forward controllers for oxygen starvation control of PEM fuel cell stacks. Int. J. Model. Identif. Control. 19(4): 352-360 (2013) - [j25]Adnan Hamad, Dong-Ya Zhao, Dingli Yu, Quan Min Zhu:
On-board monitoring of air path for automotive IC engines. Int. J. Model. Identif. Control. 20(1): 1-15 (2013) - [c19]Abdelkarim M. Ertiame, Dingli Yu, Feng Yu, J. B. Gomm:
Fault detection and isolation for open-loop Chylla-Haase polymerization reactor. ICAC 2013: 1-6 - [c18]M. K. Mahanijah, D. W. Yu, D. L. Yu:
Fault detection and isolation based on feedforward-feedback control for oxygen excess of fuel cell stack. ICAC 2013: 1-5 - [c17]Magdi M. Nabi, Dingli Yu, Feng Yu:
RBF model based predictive control for exothermic semi-batch polymerizations. ICAC 2013: 1-5 - 2011
- [c16]Omar Ragb, Karl O. Jones, Dingli Yu, J. Barry Gomm:
Adaptive feed-forward and feedback control using neural networks for oxygen ratio in fuel cell stacks. CompSysTech 2011: 323-328 - [c15]Adnan Hamad, Karl O. Jones, Dingli Yu, J. B. Gomm, Mahavir S. Sangha:
Residual generation for fault detection of internal combustion engine. CompSysTech 2011: 329-334 - 2010
- [j24]Yu-Jia Zhai, Ding-Wen Yu, Hong-Yu Guo, Ding-Li Yu:
Robust air/fuel ratio control with adaptive DRNN model and AD tuning. Eng. Appl. Artif. Intell. 23(2): 283-289 (2010)
2000 – 2009
- 2009
- [j23]Yu-Jia Zhai, Ding-Li Yu:
Neural network model-based automotive engine air/fuel ratio control and robustness evaluation. Eng. Appl. Artif. Intell. 22(2): 171-180 (2009) - 2008
- [j22]Mahavir S. Sangha, Dingli Yu, J. Barry Gomm:
Robustness assessment and adaptive FDI for car engine. Int. J. Autom. Comput. 5(2): 109-118 (2008) - [j21]Mahavir S. Sangha, J. Barry Gomm, Dingli Yu:
Neural network fault classification of transient data in an automotive engine air path. Int. J. Model. Identif. Control. 3(2): 148-155 (2008) - [j20]Shiwei Wang, D. L. Yu:
Adaptive RBF network for parameter estimation and stable air-fuel ratio control. Neural Networks 21(1): 102-112 (2008) - 2007
- [j19]Ding-Li Yu, Ding-Wen Yu:
A new structure adaptation algorithm for RBF networks and its application. Neural Comput. Appl. 16(1): 91-100 (2007) - [c14]Shiwei Wang, D. L. Yu:
Robust Integral Sliding Mode Control against Matched and Unmatched System Uncertainty. IMECS 2007: 1483-1488 - [c13]Shiwei Wang, D. L. Yu:
A New Fuel Injection Control Solution via Simple and Adaptive Sliding Mode. IMECS 2007: 1528-1535 - [c12]Shiwei Wang, Dingli Yu:
Neural Network in Stable Adaptive Control Law for Automotive Engines. ISNN (1) 2007: 122-131 - [c11]Yu-Jia Zhai, Ding-Li Yu:
A Neural Network Model Based MPC of Engine AFR with Single-Dimensional Optimization. ISNN (1) 2007: 339-348 - [c10]D. L. Yu, T. K. Chang, D. W. Yu:
An On-Line Learning Algorithm of Parallel Mode for MLPN Models. ISNN (2) 2007: 432-437 - 2006
- [j18]S. W. Wang, D. L. Yu, J. B. Gomm, G. F. Page, S. S. Douglas:
Adaptive neural network model based predictive control for air-fuel ratio of SI engines. Eng. Appl. Artif. Intell. 19(2): 189-200 (2006) - [j17]Ding-Li Yu, Ding-Wen Yu, J. Barry Gomm:
Neural model adaptation and predictive control of a chemical process rig. IEEE Trans. Control. Syst. Technol. 14(5): 828-840 (2006) - [c9]Shiwei Wang, D. L. Yu:
Neural Network Parameter Adaptation for a Fuel Injection Control System. CCECE 2006: 558-561 - [c8]Shiwei Wang, D. L. Yu:
An Application of Second-Order Sliding Mode Control for IC Engine Fuel Injection. CCECE 2006: 1035-1038 - [c7]Ding-Li Yu, Thoonkhin Chang:
Fault Diagnosis with Enhanced Neural Network Modelling. ISNN (2) 2006: 358-363 - [c6]Ding-Wen Yu, Ding-Li Yu:
Adaptive Pseudo Linear RBF Model for Process Control. ISNN (2) 2006: 1013-1018 - 2005
- [j16]D. L. Yu, T. K. Chang, D. W. Yu:
Adaptive neural model-based fault tolerant control for multi-variable processes. Eng. Appl. Artif. Intell. 18(4): 393-411 (2005) - [j15]Shiwei Wang, Ding-Li Yu:
Adaptive air-fuel ratio control with MLP network. Int. J. Autom. Comput. 2(2): 125-133 (2005) - [j14]Dingli Yu, T. Chang:
Adaptation of diagonal recurrent neural network model. Neural Comput. Appl. 14(3): 189-197 (2005) - [j13]Ding-Li Yu, Thoonkhin Chang, Ding-Wen Yu:
Fault tolerant control of multivariable processes using auto-tuning PID controller. IEEE Trans. Syst. Man Cybern. Part B 35(1): 32-43 (2005) - [c5]Ding-Li Yu, Thoonkhin Chang, Jin Wang:
Fault Tolerant Control of Nonlinear Processes with Adaptive Diagonal Recurrent Neural Network Model. ISNN (3) 2005: 86-91 - [c4]Ding-Li Yu, Ding-Wen Yu:
Detecting Sensor Faults for a Chemical Reactor Rig via Adaptive Neural Network Model. ISNN (3) 2005: 544-549 - [c3]Ding-Li Yu, Michael Beham:
Comparative Study on Engine Torque Modelling Using Different Neural Networks. ISNN (3) 2005: 865-870 - 2004
- [j12]Thoonkhin Chang, Ding-Li Yu, Ding-Wen Yu:
Neural network model adaptation and its application to process control. Adv. Eng. Informatics 18(1): 1-8 (2004) - [j11]Dingli Yu:
A Localized Forgetting Method for Gaussian RBFN Model Adaptation. Neural Process. Lett. 20(2): 125-135 (2004) - 2003
- [j10]Ding-Li Yu, Ding-Wen Yu:
A linear parameter-varying radial basis function model and predictive control of a chemical reactor. Int. J. Syst. Sci. 34(14-15): 747-761 (2003) - [j9]Ding-Wen Yu, Ding-Li Yu:
Neural network control of multivariable processes with a fast optimisation algorithm. Neural Comput. Appl. 12(3-4): 185-189 (2003) - 2002
- [j8]D. L. Yu, J. B. Gomm:
Enhanced Neural Network Modelling for a Real Multi-variable Chemical Process. Neural Comput. Appl. 10(4): 289-299 (2002) - 2001
- [j7]D. L. Yu, Derek Nicholas Shields:
Extension of the parity-space method to fault diagnosis of bilinear systems. Int. J. Syst. Sci. 32(8): 953-962 (2001) - 2000
- [j6]J. B. Gomm, D. L. Yu:
Order and delay selection for neural network modelling by identification of linearized models. Int. J. Syst. Sci. 31(10): 1273-1283 (2000) - [j5]Ding-Li Yu:
Diagnosing simulated faults for an industrial furnace based on bilinear model. IEEE Trans. Control. Syst. Technol. 8(3): 435-442 (2000) - [j4]J. Barry Gomm, D. L. Yu:
Selecting radial basis function network centers with recursive orthogonal least squares training. IEEE Trans. Neural Networks Learn. Syst. 11(2): 306-314 (2000)
1990 – 1999
- 1997
- [j3]D. L. Yu, J. B. Gomm, D. Williams:
A Recursive Orthogonal Least Squares Algorithm for Training RBF Networks. Neural Process. Lett. 5(3): 167-176 (1997) - 1996
- [j2]D. L. Yu, Derek Nicholas Shields:
A bilinear fault detection observer. Autom. 32(11): 1597-1602 (1996) - [j1]Dingli Yu, Derek Nicholas Shields, Steve Daley:
A Hybrid Fault Diagnosis Approach Using Neural Networks. Neural Comput. Appl. 4(1): 21-26 (1996) - 1995
- [c2]Dingli Yu, Derek Nicholas Shields, Steve Daley:
Application of Radial Basis Function Networks to Fault Diagnosis for a Hydraulic System. ICANNGA 1995: 100-103 - [c1]Dingli Yu, Derek Nicholas Shields:
Optimally Robust Fault Diagnosis Using Genetic Algorithms. ICANNGA 1995: 104-107
Coauthor Index
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