Fuzzy Output Support Vector Machines for Classification. - Zongxia Xie; Qinghua Hu; Daren Yu (ICNC (3), 2005)

Hybrid Attribute Reduction for Classification Based on A Fuzzy Rough Set Technique. - Qinghua Hu; Daren Yu; Zongxia Xie (SDM, 2005)

Improved Feature Selection Algorithm Based on SVM and Correlation. - Zongxia Xie; Qinghua Hu; Daren Yu (ISNN (1), 2006)

Information-preserving hybrid data reduction based on fuzzy-rough techniques. - Qinghua Hu; Daren Yu; Zongxia Xie (Pattern Recognit. Lett., 2006)

Fuzzy Probabilistic Approximation Spaces and Their Information Measures. - Qinghua Hu; Daren Yu; Zongxia Xie; Jinfu Liu (IEEE Trans. Fuzzy Syst., 2006)

Consistency Based Attribute Reduction. - Qinghua Hu; Hui Zhao; Zongxia Xie; Daren Yu (PAKDD, 2007)

Selecting Samples and Features for SVM Based on Neighborhood Model. - Qinghua Hu; Daren Yu; Zongxia Xie (RSFDGrC, 2007)

A Hybrid Method for Forecasting Stock Market Trend Using Soft-Thresholding De-noise Model and SVM. - Xueshen Sui; Qinghua Hu; Daren Yu; Zongxia Xie; Zhongying Qi (RSFDGrC, 2007)

Hybrid attribute reduction based on a novel fuzzy-rough model and information granulation. - Qinghua Hu; Zongxia Xie; Daren Yu (Pattern Recognit., 2007)

EROS: Ensemble rough subspaces. - Qinghua Hu; Daren Yu; Zongxia Xie; Xiaodong Li (Pattern Recognit., 2007)

Neighborhood classifiers. - Qinghua Hu; Daren Yu; Zongxia Xie (Expert Syst. Appl., 2008)

Comments on "Fuzzy Probabilistic Approximation Spaces and Their Information Measures". - Qinghua Hu; Zongxia Xie; Daren Yu (IEEE Trans. Fuzzy Syst., 2008)

Visual Object Recognition with Bagging of One Class Support Vector Machines. - Zongxia Xie; Yong Xu 007; Qinghua Hu (IBICA, 2011)

Neighborhood based sample and feature selection for SVM classification learning. - Qiang He 003; Zongxia Xie; Qinghua Hu; Congxin Wu (Neurocomputing, 2011)

Margin distribution based bagging pruning. - Zongxia Xie; Yong Xu 007; Qinghua Hu; Pengfei Zhu 001 (Neurocomputing, 2012)

Sparse group LASSO based uncertain feature selection. - Zongxia Xie; Yong Xu 007 (Int. J. Mach. Learn. Cybern., 2014)

Noise model based v-support vector regression with its application to short-term wind speed forecasting. - Qinghua Hu; Shiguang Zhang; Zongxia Xie; Ju-Sheng Mi; Jie Wan (Neural Networks, 2014)

Kernel ridge regression for general noise model with its application. - Shiguang Zhang; Qinghua Hu; Zongxia Xie; Ju-Sheng Mi (Neurocomputing, 2015)

基于监督学习的日冕暗化检测与提取算法 (Coronal Dimming Detecting and Extracting Algorithm Based on Supervised Learning). - Hongmei Tian; Bo Peng 006; Tianrui Li 001; Zongxia Xie (计算机科学, 2015)

Locally Weighted Ensemble Learning for Regression. - Man Yu; Zongxia Xie; Hong Shi; Qinghua Hu (PAKDD (1), 2016)

A Pixel-to-Pixel Convolutional Neural Network for Single Image Dehazing. - Chengkai Zhu; Yucan Zhou; Zongxia Xie (ICONIP (3), 2017)

Joint L1-L2 Regularisation for Blind Speech Deconvolution. - Jian Guan 001; Xuan Wang 002; Zongxia Xie; Shuhan Qi; Wenwu Wang 001 (PCM (1), 2017)

Uncertain data classification with additive kernel support vector machine. - Zongxia Xie; Yong Xu 007; Qinghua Hu (Data Knowl. Eng., 2018)

Composite Quantile Regression Long Short-Term Memory Network. - Zongxia Xie; Hao Wen (ICANN (4), 2019)

Large-scale support vector regression with budgeted stochastic gradient descent. - Zongxia Xie; Yingda Li (Int. J. Mach. Learn. Cybern., 2019)

Interval prediction for time series based on LSTM and mixed Gaussian distribution. - Zongxia Xie; Renhui Li; Hui Hu (SMC, 2020)

Emitting Word Timings with HMM-Free End-to-End System in Automatic Speech Recognition. - Xianzhao Chen; Hao Ni; Yi He; Kang Wang; Zejun Ma; Zongxia Xie (Interspeech, 2021)

ALGeNet: Adaptive Log-Euclidean Gaussian embedding network for time series forecasting. - Zongxia Xie; Hui Hu; Qilong Wang 001; Renhui Li (Neurocomputing, 2021)

Uncertainty prediction and calibration using multi-expert gating mechanism. - Kun Cao; Zongxia Xie (IJCNN, 2022)

Multi-channel fusion graph neural network for multivariate time series forecasting. - Yanzhe Chen; Zongxia Xie (J. Comput. Sci., 2022)

Majorities help minorities: Hierarchical structure guided transfer learning for few-shot fault recognition. - Hao Chen; Ruonan Liu; Zongxia Xie; Qinghua Hu; Jianhua Dai; Junhai Zhai (Pattern Recognit., 2022)

AFRF: Angle Feature Retrieval Based Popularity Forecasting. - Haoyu Wang; Zongxia Xie; Meiyao Liu; Canhua Guan (CIKM, 2023)

Dual-resolution transformer combined with multi-layer separable convolution fusion network for real-time semantic segmentation. - Kaidi Hu; Zongxia Xie; Qinghua Hu (Comput. Graph., 2024)

Learning Pattern-Specific Experts for Time Series Forecasting Under Patch-level Distribution Shift. - Yanru Sun; Zongxia Xie; Emadeldeen Eldele; Dongyue Chen; Qinghua Hu; Min Wu 008 (CoRR, 2024)

Lightweight convolutional neural networks with context broadcast transformer for real-time semantic segmentation. - Kaidi Hu; Zongxia Xie; Qinghua Hu (Image Vis. Comput., 2024)

ULAF-Net: Ultra lightweight attention fusion network for real-time semantic segmentation. - Kaidi Hu; Zongxia Xie; Qinghua Hu (Int. J. Mach. Learn. Cybern., 2024)

Bayesian Hierarchical Graph Neural Networks With Uncertainty Feedback for Trustworthy Fault Diagnosis of Industrial Processes. - Dongyue Chen; Zongxia Xie; Ruonan Liu; Wenlong Yu; Qinghua Hu; Xianling Li; Steven X. Ding (IEEE Trans. Neural Networks Learn. Syst., 2024)

Hierarchical Classification Auxiliary Network for Time Series Forecasting. - Yanru Sun; Zongxia Xie; Dongyue Chen; Emadeldeen Eldele; Qinghua Hu (AAAI, 2025)

Frequency-Domain Popularity Forecasting with Shape-Based Retrieval. - Canhua Guan; Zongxia Xie; Haoyu Wang; Haoyu Xing (ICASSP, 2025)

Patch-wise Structural Loss for Time Series Forecasting. - Dilfira Kudrat; Zongxia Xie; Yanru Sun; Tianyu Jia; Qinghua Hu (CoRR, 2025)

Lightweight Channel-wise Dynamic Fusion Model: Non-stationary Time Series Forecasting via Entropy Analysis. - Tianyu Jia; Zongxia Xie; Yanru Sun; Dilfira Kudrat; Qinghua Hu (CoRR, 2025)

LangTime: A Language-Guided Unified Model for Time Series Forecasting with Proximal Policy Optimization. - Wenzhe Niu; Zongxia Xie; Yanru Sun; Wei He; Man Xu; Chao Hao (CoRR, 2025)

Adapting LLMs to Time Series Forecasting via Temporal Heterogeneity Modeling and Semantic Alignment. - Yanru Sun; Emadeldeen Eldele; Zongxia Xie; Yucheng Wang 001; Wenzhe Niu; Qinghua Hu; Chee Keong Kwoh 001; Min Wu 008 (CoRR, 2025)

PPGF: Probability Pattern-Guided Time Series Forecasting. - Yanru Sun; Zongxia Xie; Haoyu Xing; Hualong Yu; Qinghua Hu (IEEE Trans. Neural Networks Learn. Syst., 2025)