Improved CBP Neural Network Model with Applications in Time Series Prediction. - Qun Dai; Songcan Chen; Benzhu Zhang (Neural Process. Lett., 2003)

Discounted least squares-improved circular back-propogation neural networks with applications in time series prediction. - Songcan Chen; Qun Dai (Neural Comput. Appl., 2005)

Chained DLS-ICBP Neural Networks with Multiple Steps Time Series Prediction. - Qun Dai; Songcan Chen (Neural Process. Lett., 2005)

Integrating the improved CBP model with kernel SOM. - Qun Dai; Songcan Chen (Neurocomputing, 2006)

The build of a dynamic classifier selection ICBP system and its application to pattern recognition. - Qun Dai (Neural Comput. Appl., 2010)

The build of n-Bits Binary Coding ICBP Ensemble System. - Qun Dai; Ningzhong Liu (Neurocomputing, 2011)

Alleviating the problem of local minima in Backpropagation through competitive learning. - Qun Dai; Ningzhong Liu (Neurocomputing, 2012)

Relationship between Mean Radiant Temperature and Building Type for Pedestrians in Rotterdam. - Qun Dai; Marc Aurel Schnabel (CAAD Futures, 2013)

Back-propagation with diversive curiosity: An automatic conversion from search stagnation to exploration. - Qun Dai (Appl. Soft Comput., 2013)

ModEnPBT: A Modified Backtracking Ensemble Pruning algorithm. - Qun Dai; Zhuan Liu (Appl. Soft Comput., 2013)

A novel ensemble pruning algorithm based on randomized greedy selective strategy and ballot. - Qun Dai (Neurocomputing, 2013)

A competitive ensemble pruning approach based on cross-validation technique. - Qun Dai (Knowl. Based Syst., 2013)

An efficient ensemble pruning algorithm using One-Path and Two-Trips searching approach. - Qun Dai (Knowl. Based Syst., 2013)

Ensemble selection by GRASP. - Zhuan Liu; Qun Dai; Ningzhong Liu (Appl. Intell., 2014)

A two-phased and Ensemble scheme integrated Backpropagation algorithm. - Qun Dai; Zhongchen Ma; Qiongyu Xie (Appl. Soft Comput., 2014)

Introducing randomness into greedy ensemble pruning algorithms. - Qun Dai; Meiling Li (Appl. Intell., 2015)

Extreme learning machines' ensemble selection with GRASP. - Ting Zhang; Qun Dai; Zhongchen Ma (Appl. Intell., 2015)

A new reverse reduce-error ensemble pruning algorithm. - Qun Dai; Ting Zhang; Ningzhong Liu (Appl. Soft Comput., 2015)

Several novel evaluation measures for rank-based ensemble pruning with applications to time series prediction. - Zhongchen Ma; Qun Dai; Ningzhong Liu (Expert Syst. Appl., 2015)

An efficient ordering-based ensemble pruning algorithm via dynamic programming. - Qun Dai; Xiaomeng Han (Appl. Intell., 2016)

Hybrid ensemble selection algorithm incorporating GRASP with path relinking. - Ting Zhang; Qun Dai (Appl. Intell., 2016)

Local well-posedness for Boussinesq approximation with shear dependent viscosities in 3D. - Changjia Wang; Qun Dai (Comput. Math. Appl., 2016)

A novel Supervised Competitive Learning algorithm. - Qun Dai; Gang Song (Neurocomputing, 2016)

Selected an Stacking ELMs for Time Series Prediction. - Zhongchen Ma; Qun Dai (Neural Process. Lett., 2016)

A hierarchical and parallel branch-and-bound ensemble selection algorithm. - Qun Dai; ChangSheng Yao (Appl. Intell., 2017)

Considering diversity and accuracy simultaneously for ensemble pruning. - Qun Dai; Rui Ye 003; Zhuan Liu (Appl. Soft Comput., 2017)

A novel double deep ELMs ensemble system for time series forecasting. - Gang Song; Qun Dai (Knowl. Based Syst., 2017)

Batch-normalized Mlpconv-wise supervised pre-training network in network. - Xiaomeng Han; Qun Dai (Appl. Intell., 2018)

A novel knowledge-leverage-based transfer learning algorithm. - Meiling Li; Qun Dai (Appl. Intell., 2018)

A novel transfer learning framework for time series forecasting. - Rui Ye 003; Qun Dai (Knowl. Based Syst., 2018)

A Novel Greedy Randomized Dynamic Ensemble Selection Algorithm. - Rui Ye 003; Qun Dai (Neural Process. Lett., 2018)

A new dual weights optimization incremental learning algorithm for time series forecasting. - Jinhua Li; Qun Dai (Appl. Intell., 2019)

MultiTL-KELM: A multi-task learning algorithm for multi-step-ahead time series prediction. - Rui Ye 003; Qun Dai (Appl. Soft Comput., 2019)

Two novel hybrid Self-Organizing Map based emotional learning algorithms. - Qun Dai; Lin Guo (Neural Comput. Appl., 2019)

A novel double incremental learning algorithm for time series prediction. - Jinhua Li; Qun Dai; Rui Ye 003 (Neural Comput. Appl., 2019)

Several Novel Dynamic Ensemble Selection Algorithms for Time Series Prediction. - ChangSheng Yao; Qun Dai; Gang Song (Neural Process. Lett., 2019)

A hybrid transfer learning algorithm incorporating TrSVM with GASEN. - Rui Ye 003; Qun Dai; Meiling Li (Pattern Recognit., 2019)

Two novel ELM-based stacking deep models focused on image recognition. - Gang Song; Qun Dai; Xiaomeng Han; Lin Guo (Appl. Intell., 2020)

DeepCascade-WR: a cascading deep architecture based on weak results for time series prediction. - Chunyang Zhang; Qun Dai; Gang Song (Int. J. Mach. Learn. Cybern., 2020)

A novel active multi-source transfer learning algorithm for time series forecasting. - Qitao Gu; Qun Dai (Appl. Intell., 2021)

EnsPKDE&IncLKDE: a hybrid time series prediction algorithm integrating dynamic ensemble pruning, incremental learning, and kernel density estimation. - Gangliang Zhu; Qun Dai (Appl. Intell., 2021)

Integrating Multi-Source Transfer Learning, Active Learning and Metric Learning paradigms for Time Series Prediction. - Qitao Gu; Qun Dai; HuiHui Yu; Rui Ye 003 (Appl. Soft Comput., 2021)

Laplacian regularized low-rank sparse representation transfer learning. - Lin Guo; Qun Dai (Int. J. Mach. Learn. Cybern., 2021)

DEP-TSPmeta: a multiple criteria Dynamic Ensemble Pruning technique ad-hoc for time series prediction. - Jing Zhang 092; Qun Dai; ChangSheng Yao (Int. J. Mach. Learn. Cybern., 2021)

Implementing transfer learning across different datasets for time series forecasting. - Rui Ye 003; Qun Dai (Pattern Recognit., 2021)

A deep multivariate time series multistep forecasting network. - Chenrui Yin; Qun Dai (Appl. Intell., 2022)

DWE-IL: a new incremental learning algorithm for non-stationary time series prediction via dynamically weighting ensemble learning. - HuiHui Yu; Qun Dai (Appl. Intell., 2022)

A novel deep pixel restoration video prediction algorithm integrating attention mechanism. - Muxuan Yuan; Qun Dai (Appl. Intell., 2022)

A self-supervised COVID-19 CT recognition system with multiple regularizations. - Han Lu; Qun Dai (Comput. Biol. Medicine, 2022)

A relationship-aligned transfer learning algorithm for time series forecasting. - Rui Ye 003; Qun Dai (Inf. Sci., 2022)

End-to-end variational graph clustering with local structural preservation. - Lin Guo; Qun Dai (Neural Comput. Appl., 2022)

A cost-sensitive active learning algorithm: toward imbalanced time series forecasting. - Jing Zhang 092; Qun Dai (Neural Comput. Appl., 2022)

Latent adversarial regularized autoencoder for high-dimensional probabilistic time series prediction. - Jing Zhang 092; Qun Dai (Neural Networks, 2022)

Graph Clustering via Variational Graph Embedding. - Lin Guo; Qun Dai (Pattern Recognit., 2022)

PlanRanker: Towards Personalized Ranking of Train Transfer Plans. - Jia Xu 005; Wanjie Tao; Zulong Chen; Jin Huang 001; Huihui Liu; Hong Wen 002; Shenghua Ni; Qun Dai; Yu Gu 002 (KDD, 2023)

Event-Aware Adaptive Clustering Uplift Network for Insurance Creative Ranking. - Wanjie Tao; Huihui Liu; Xuqi Li; Qun Dai; Hong Wen 002; Zulong Chen (SIGIR, 2023)

Adversarial unsupervised domain adaptation based on generative adversarial network for stock trend forecasting. - Qiheng Wei; Qun Dai (Intell. Data Anal., 2023)

An active learning-based incremental deep-broad learning algorithm for unbalanced time series prediction. - Xin Shen; Qun Dai; Wusat Ullah (Inf. Sci., 2023)

MrCAN: Multi-relations aware convolutional attention network for multivariate time series forecasting. - Jing Zhang 092; Qun Dai (Inf. Sci., 2023)

Deep Pixel Restoration Loop Coding Network [Application Notes] [Application Notes]. - Tianxiang Wang; Qun Dai; Muxuan Yuan (IEEE Comput. Intell. Mag., 2023)

AE-DIL: A double incremental learning algorithm for non-stationary time series prediction via adaptive ensemble. - HuiHui Yu; Qun Dai (Inf. Sci., 2023)

Dynamic ensemble pruning algorithms fusing meta-learning with heuristic parameter optimization for time series prediction. - Xin Shen; Qun Dai; Gangliang Zhu; Jing Zhang (Expert Syst. Appl., 2023)

SURVS: A Swin-Unet and game theory-based unsupervised segmentation method for retinal vessel. - Tianxiang Wang; Qun Dai (Comput. Biol. Medicine, 2023)

Unified Unsupervised Salient Object Detection via Knowledge Transfer. - Yao Yuan; Wutao Liu; Pan Gao; Qun Dai; Jie Qin (IJCAI, 2024)

GrokLST: Towards High-Resolution Benchmark and Toolkit for Land Surface Temperature Downscaling. - Qun Dai; Chunyang Yuan; Yimian Dai; Yuxuan Li 004; Xiang Li 041; Kang Ni; Jianhui Xu; Xiangbo Shu; Jian Yang 003 (CoRR, 2024)

A patch distribution-based active learning method for multiple instance Alzheimer's disease diagnosis. - Tianxiang Wang; Qun Dai (Pattern Recognit., 2024)

Self-supervised multi-task learning for medical image analysis. - Huihui Yu; Qun Dai (Pattern Recognit., 2024)

Differential Attention Orientated Cascade Network for Infrared Small Target Detection. - Wenjuan Tang; Qun Dai; Fan Hao (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024)

An Efficient Knowledge Distillation-Based Detection Method for Infrared Small Targets. - Wenjuan Tang; Qun Dai; Fan Hao (Remote. Sens., 2024)

Collaboration or Competition: An Infomax-Based Period-Aware Transformer for Ticket-Grabbing Prediction. - Wanjie Tao; Huihui Liu; Jia Xu 005; Qun Dai; Jing Zhou; Hong Wen 002; Zulong Chen (IEEE Trans. Intell. Transp. Syst., 2024)

Dynamic Topic Segmentation in Dialogues: Enhancing Boundaries with Topic-Aware Propagation. - Yantong Lv; Wanjie Tao; Qun Dai; Zulong Chen; Quan Lu; Ning Jiang (WWW (Companion Volume), 2025)

A self-supervised semi-supervised echocardiographic video left ventricle segmentation method. - Tianxiang Wang; Qun Dai (Biomed. Signal Process. Control., 2025)

Attribute reduction using self-information uncertainty measures in optimistic neighborhood extreme-granulation rough set. - Kanglin Qu; Pan Gao; Qun Dai; Yuanhao Sun; Xu Hua (Inf. Sci., 2025)

Escarcitys: A framework for enhancing medical image classification performance in scarcity of trainable samples scenarios. - Tianxiang Wang; Qun Dai; Wei Xiong (Neural Networks, 2025)

MoCoLSK: Modality-Conditioned High-Resolution Downscaling for Land Surface Temperature. - Qun Dai; Chunyang Yuan; Yimian Dai; Yuxuan Li 004; Xiang Li 041; Kang Ni; Jianhui Xu; Xiangbo Shu; Jian Yang 003 (IEEE Trans. Geosci. Remote. Sens., 2025)

Uncertainty-Guided Refinement for Fine-Grained Salient Object Detection. - Yao Yuan; Pan Gao 001; Qun Dai; Jie Qin; Wei Xiang 001 (IEEE Trans. Image Process., 2025)

A 3D-CNN and multi-loss video prediction architecture. - Ziru Qin; Qun Dai (Appl. Intell., 2025)

HydraMamba: Multi-Head State Space Model for Global Point Cloud Learning. - Kanglin Qu; Pan Gao; Qun Dai; Yuanhao Sun (CoRR, 2025)

A Data-Level Augmentation Framework for Time Series Forecasting With Ambiguously Related Source Data. - Rui Ye 003; Qun Dai (IEEE Trans. Knowl. Data Eng., 2025)

CE-AH: A contrast-enhanced attention hierarchical network for Alzheimer's disease diagnosis based on structural MRI. - Tianxiang Wang; Qun Dai; Han Lu (Pattern Recognit., 2026)