Liangxiao Jiang

140 papers A* 10A 3B 11C 4Misc 1Journal 98Unranked 13
YearRankTypeTitle / Venue / Authors
2026 J jnl
Category-aware dual graph disentanglement with multi-task learning for session-based recommendation.
Appl. Soft Comput.
Hongxia Ye, Chaoqun Li, Liangxiao Jiang
2026 J jnl
Confident learning-based noise correction for crowdsourcing.
Pattern Recognit.
Bingrui Su, Liangxiao Jiang, Shanshan Si
2026 J jnl
Cross-session interest extraction for recommendation.
Expert Syst. Appl.
Jin Jin, Chaoqun Li, Liangxiao Jiang
2026 J jnl
Invisible poisoning attack on recommender systems based on multi-view uniformity.
Inf. Sci.
Sijian Huang, Chaoqun Li, Liangxiao Jiang
2026 J jnl
Supervised learning-based label integration for crowdsourcing.
Pattern Recognit.
Renping Di, Liangxiao Jiang, Shanshan Si, Kun Yue
2025 J jnl
Cross-worker joint modeling-based label integration for crowdsourcing.
Int. J. Approx. Reason.
Can Pan, Liangxiao Jiang, Shanshan Si
2025 J jnl
Dual-View Learning from Crowds.
ACM Trans. Knowl. Discov. Data
Huan Zhang, Liangxiao Jiang, Wenjun Zhang, Geoffrey I. Webb
2025 J jnl
ELDP: Enhanced Label Distribution Propagation for Crowdsourcing.
IEEE Trans. Pattern Anal. Mach. Intell.
Wenjun Zhang, Liangxiao Jiang, Chaoqun Li
2025 A* conf
Instance Correlation Graph-based Naive Bayes.
ICML
Chengyuan Li, Liangxiao Jiang, Wenjun Zhang, Liangjun Yu, Huan Zhang
2025 J jnl
Intent-aware Recommendation Based on Principal Component Analysis.
ACM Trans. Knowl. Discov. Data
Yuyan Ai, Chaoqun Li, Liangxiao Jiang
2025 J jnl
Label Consistency-Based Ground Truth Inference for Crowdsourcing.
IEEE Trans. Neural Networks Learn. Syst.
Jiao Li, Liangxiao Jiang, Wenjun Zhang
2025 A* conf
Label Distribution Propagation-based Label Completion for Crowdsourcing.
ICML
Tong Wu, Liangxiao Jiang, Wenjun Zhang, Chaoqun Li
2025 J jnl
Learning From Crowds by Class-Specific Instance Weighting.
IEEE Trans. Emerg. Top. Comput. Intell.
Qiang Ji, Liangxiao Jiang, Wenjun Zhang, Chaoqun Li
2025 A* conf
TLLC: Transfer Learning-based Label Completion for Crowdsourcing.
ICML
Wenjun Zhang, Liangxiao Jiang, Chaoqun Li
2025 J jnl
Three-way decision-based label integration for crowdsourcing.
Pattern Recognit.
Can Pan, Liangxiao Jiang, Chaoqun Li
2025 J jnl
WirMAE: Learning Well-Logging Interval Representations via Masked Autoencoders for Gas Hydrate Reservoir Characterization.
IEEE Trans. Geosci. Remote. Sens.
Zikun Li, Zhun Zhang, Liangxiao Jiang, Zhichao Liu, Hang Zhou, Jiaxin Sun, Kyungbook Lee, Fulong Ning
2025 J jnl
Worker Similarity-Based Label Completion for Crowdsourcing.
IEEE Trans. Big Data
Xue Wu, Liangxiao Jiang, Wenjun Zhang, Chaoqun Li
2024 J jnl
Certainty weighted voting-based noise correction for crowdsourcing.
Pattern Recognit.
Huiru Li, Liangxiao Jiang, Chaoqun Li
2024 J jnl
DDRANet: A Dynamic Density-Region-Aware Network for Crowd Counting.
IEEE Signal Process. Lett.
Mengqi Lei, Haochen Wu, Xinhua Lv, Liangxiao Jiang
2024 J jnl
FNNWV: farthest-nearest neighbor-based weighted voting for class-imbalanced crowdsourcing.
Sci. China Inf. Sci.
Wenjun Zhang, Liangxiao Jiang, Ziqi Chen, Chaoqun Li
2024 A* conf
IWBVT: Instance Weighting-based Bias-Variance Trade-off for Crowdsourcing.
NeurIPS
Wenjun Zhang, Liangxiao Jiang, Chaoqun Li
2024 J jnl
Instance redistribution-based label integration for crowdsourcing.
Inf. Sci.
Yao Zhang, Liangxiao Jiang, Chaoqun Li
2024 A* conf
KFNN: K-Free Nearest Neighbor For Crowdsourcing.
NeurIPS
Wenjun Zhang, Liangxiao Jiang, Chaoqun Li
2024 A conf
Label Consistency-based Worker Filtering for Crowdsourcing.
UAI
Jiao Li, Liangxiao Jiang, Chaoqun Li, Wenjun Zhang
2024 J jnl
Label distribution similarity-based noise correction for crowdsourcing.
Frontiers Comput. Sci.
Lijuan Ren, Liangxiao Jiang, Wenjun Zhang, Chaoqun Li
2024 A conf
Learning from Crowds with Dual-View K-Nearest Neighbor.
UAI
Jiao Li, Liangxiao Jiang, Xue Wu, Wenjun Zhang
2024 A* conf
Probabilistic Matrix Factorization-based Three-stage Label Completion for Crowdsourcing.
ICDM
Boyi Yang, Liangxiao Jiang, Wenjun Zhang
2024 J jnl
Token-disentangling Mutual Transformer for multimodal emotion recognition.
Eng. Appl. Artif. Intell.
Guanghao Yin, Yuanyuan Liu, Tengfei Liu, Haoyu Zhang, Fang Fang, Chang Tang, Liangxiao Jiang
2024 J jnl
Weighted Adversarial Learning From Crowds.
IEEE Trans. Serv. Comput.
Ziqi Chen, Liangxiao Jiang, Wenjun Zhang, Chaoqun Li
2024 J jnl
Worker similarity-based noise correction for crowdsourcing.
Inf. Syst.
Yufei Hu, Liangxiao Jiang, Wenjun Zhang
2023 J jnl
A multi-view-based noise correction algorithm for crowdsourcing learning.
Inf. Fusion
Xinyang Li, Chaoqun Li, Liangxiao Jiang
2023 J jnl
Attribute augmentation-based label integration for crowdsourcing.
Frontiers Comput. Sci.
Yao Zhang, Liangxiao Jiang, Chaoqun Li
2023 J jnl
Dual-View Noise Correction for Crowdsourcing.
IEEE Internet Things J.
Qiang Ji, Liangxiao Jiang, Wenjun Zhang
2023 A conf
Hierarchical Attention Learning for Multimodal Classification.
ICME
Xin Zou, Chang Tang, Wei Zhang, Kun Sun, Liangxiao Jiang
2023 J jnl
Improving label quality in crowdsourcing using deep co-teaching-based noise correction.
Int. J. Mach. Learn. Cybern.
Kang Zhu, Siqing Xue, Liangxiao Jiang
2023 — conf
Instance Weighting-Based Noise Correction for Crowdsourcing.
ICIC (4)
Qiang Ji, Liangxiao Jiang, Wenjun Zhang
2023 J jnl
Instance difficulty-based noise correction for crowdsourcing.
Expert Syst. Appl.
Yufei Hu, Liangxiao Jiang, Chaoqun Li
2023 J jnl
Label confidence-based noise correction for crowdsourcing.
Eng. Appl. Artif. Intell.
Lijuan Ren, Liangxiao Jiang, Chaoqun Li
2023 J jnl
Learning from crowds with robust logistic regression.
Inf. Sci.
Wenbin Li, Chaoqun Li, Liangxiao Jiang
2023 J jnl
Learning from crowds with robust support vector machines.
Sci. China Inf. Sci.
Wenjun Yang, Chaoqun Li, Liangxiao Jiang
2023 J jnl
Multi-View Attribute Weighted Naive Bayes.
IEEE Trans. Knowl. Data Eng.
Huan Zhang, Liangxiao Jiang, Wenjun Zhang, Chaoqun Li
2023 J jnl
Neighborhood Weighted Voting-Based Noise Correction for Crowdsourcing.
ACM Trans. Knowl. Discov. Data
Huiru Li, Liangxiao Jiang, Siqing Xue
2023 J jnl
Rigorous non-disjoint discretization for naive Bayes.
Pattern Recognit.
Huan Zhang, Liangxiao Jiang, Geoffrey I. Webb
2023 J jnl
Three-way decision-based noise correction for crowdsourcing.
Int. J. Approx. Reason.
Xue Wu, Liangxiao Jiang, Wenjun Zhang, Chaoqun Li
2022 J jnl
A novel ground truth inference algorithm based on instance similarity for crowdsourcing learning.
Appl. Intell.
Ben Ma, Chaoqun Li, Liangxiao Jiang
2022 J jnl
Attribute augmented and weighted naive Bayes.
Sci. China Inf. Sci.
Huan Zhang, Liangxiao Jiang, Chaoqun Li
2022 J jnl
Fine tuning attribute weighted naive Bayes.
Neurocomputing
Huan Zhang, Liangxiao Jiang
2022 J jnl
Improving data and model quality in crowdsourcing using co-training-based noise correction.
Inf. Sci.
Yu Dong, Liangxiao Jiang, Chaoqun Li
2022 J jnl
Label augmented and weighted majority voting for crowdsourcing.
Inf. Sci.
Ziqi Chen, Liangxiao Jiang, Chaoqun Li
2022 J jnl
Label distribution-based noise correction for multiclass crowdsourcing.
Int. J. Intell. Syst.
Ziqi Chen, Liangxiao Jiang, Chaoqun Li
2022 J jnl
Learning From Crowds With Multiple Noisy Label Distribution Propagation.
IEEE Trans. Neural Networks Learn. Syst.
Liangxiao Jiang, Hao Zhang, Fangna Tao, Chaoqun Li
2022 J jnl
Learning from crowds with decision trees.
Knowl. Inf. Syst.
Wenjun Yang, Chaoqun Li, Liangxiao Jiang
2021 J jnl
Attribute and instance weighted naive Bayes.
Pattern Recognit.
Huan Zhang, Liangxiao Jiang, Liangjun Yu
2021 J jnl
CS-ResNet: Cost-sensitive residual convolutional neural network for PCB cosmetic defect detection.
Expert Syst. Appl.
Huan Zhang, Liangxiao Jiang, Chaoqun Li
2021 J jnl
Collaboratively weighted naive Bayes.
Knowl. Inf. Syst.
Huan Zhang, Liangxiao Jiang, Chaoqun Li
2021 J jnl
Differential evolution-based weighted soft majority voting for crowdsourcing.
Eng. Appl. Artif. Intell.
Fangna Tao, Liangxiao Jiang, Chaoqun Li
2021 J jnl
Fine-grained attribute weighted inverted specific-class distance measure for nominal attributes.
Inf. Sci.
Fang Gong, Xin Wang, Liangxiao Jiang, Seyyed Mohammadreza Rahimi, Dianhong Wang
2021 J jnl
Improving data and model quality in crowdsourcing using cross-entropy-based noise correction.
Inf. Sci.
Wenqiang Xu, Liangxiao Jiang, Chaoqun Li
2021 J jnl
Modified DFS-based term weighting scheme for text classification.
Expert Syst. Appl.
Long Chen, Liangxiao Jiang, Chaoqun Li
2021 J jnl
Resampling-based noise correction for crowdsourcing.
J. Exp. Theor. Artif. Intell.
Wenqiang Xu, Liangxiao Jiang, Chaoqun Li
2021 J jnl
Using modified term frequency to improve term weighting for text classification.
Eng. Appl. Artif. Intell.
Long Chen, Liangxiao Jiang, Chaoqun Li
2021 J jnl
Wrapper Framework for Test-Cost-Sensitive Feature Selection.
IEEE Trans. Syst. Man Cybern. Syst.
Liangxiao Jiang, Ganggang Kong, Chaoqun Li
2020 J jnl
Averaged one-dependence inverted specific-class distance measure for nominal attributes.
J. Exp. Theor. Artif. Intell.
Fang Gong, Liangxiao Jiang, Dianhong Wang, Xingfeng Guo
2020 J jnl
Class-specific attribute value weighting for Naive Bayes.
Inf. Sci.
Huan Zhang, Liangxiao Jiang, Liangjun Yu
2020 J jnl
Gain ratio weighted inverted specific-class distance measure for nominal attributes.
Int. J. Mach. Learn. Cybern.
Fang Gong, Liangxiao Jiang, Huan Zhang, Dianhong Wang, Xingfeng Guo
2020 J jnl
Label similarity-based weighted soft majority voting and pairing for crowdsourcing.
Knowl. Inf. Syst.
Fangna Tao, Liangxiao Jiang, Chaoqun Li
2019 J jnl
A Correlation-Based Feature Weighting Filter for Naive Bayes.
IEEE Trans. Knowl. Data Eng.
Liangxiao Jiang, Lungan Zhang, Chaoqun Li, Jia Wu
2019 J jnl
A discriminative model selection approach and its application to text classification.
Neural Comput. Appl.
Lungan Zhang, Liangxiao Jiang, Chaoqun Li
2019 J jnl
An attribute value frequency-based instance weighting filter for naive Bayes.
J. Exp. Theor. Artif. Intell.
Wenqiang Xu, Liangxiao Jiang, Liangjun Yu
2019 J jnl
Class-specific attribute weighted naive Bayes.
Pattern Recognit.
Liangxiao Jiang, Lungan Zhang, Liangjun Yu, Dianhong Wang
2019 A* conf
Multiple Noisy Label Distribution Propagation for Crowdsourcing.
IJCAI
Hao Zhang, Liangxiao Jiang, Wenqiang Xu
2019 J jnl
Noise correction to improve data and model quality for crowdsourcing.
Eng. Appl. Artif. Intell.
Chaoqun Li, Liangxiao Jiang, Wenqiang Xu
2019 J jnl
Toward naive Bayes with attribute value weighting.
Neural Comput. Appl.
Liangjun Yu, Liangxiao Jiang, Dianhong Wang, Lungan Zhang
2019 J jnl
Two improved attribute weighting schemes for value difference metric.
Knowl. Inf. Syst.
Liangxiao Jiang, Chaoqun Li
2018 B conf
Differential Evolution-Based Weighted Majority Voting for Crowdsourcing.
PRICAI
Hao Zhang, Liangxiao Jiang, Wenqiang Xu
2018 B conf
Using Differential Evolution to Estimate Labeler Quality for Crowdsourcing.
PRICAI
Chen Qiu, Liangxiao Jiang, Zhihua Cai
2018 B conf
Weight Adjusted Naive Bayes.
ICTAI
Liangjun Yu, Liangxiao Jiang, Lungan Zhang, Dianhong Wang
2017 J jnl
Attribute Value Weighted Average of One-Dependence Estimators.
Entropy
Liangjun Yu, Liangxiao Jiang, Dianhong Wang, Lungan Zhang
2017 J jnl
Randomly selected decision tree for test-cost sensitive learning.
Appl. Soft Comput.
Chen Qiu, Liangxiao Jiang, Chaoqun Li
2017 J jnl
Toward value difference metric with attribute weighting.
Knowl. Inf. Syst.
Chaoqun Li, Liangxiao Jiang, Hongwei Li, Jia Wu, Peng Zhang
2016 J jnl
A New Feature Selection Approach to Naive Bayes Text Classifiers.
Int. J. Pattern Recognit. Artif. Intell.
Lungan Zhang, Liangxiao Jiang, Chaoqun Li
2016 J jnl
Beyond accuracy: Learning selective Bayesian classifiers with minimal test cost.
Pattern Recognit. Lett.
Ganggang Kong, Liangxiao Jiang, Chaoqun Li
2016 — conf
C4.5 or Naive Bayes: A Discriminative Model Selection Approach.
ICANN (1)
Lungan Zhang, Liangxiao Jiang, Chaoqun Li
2016 J jnl
Deep feature weighting for naive Bayes and its application to text classification.
Eng. Appl. Artif. Intell.
Liangxiao Jiang, Chaoqun Li, Shasha Wang, Lungan Zhang
2016 J jnl
Noise filtering to improve data and model quality for crowdsourcing.
Knowl. Based Syst.
Chaoqun Li, Victor S. Sheng, Liangxiao Jiang, Hongwei Li
2016 J jnl
Structure extended multinomial naive Bayes.
Inf. Sci.
Liangxiao Jiang, Shasha Wang, Chaoqun Li, Lungan Zhang
2016 J jnl
Two feature weighting approaches for naive Bayes text classifiers.
Knowl. Based Syst.
Lungan Zhang, Liangxiao Jiang, Chaoqun Li, Ganggang Kong
2015 J jnl
A Novel Minority Cloning Technique for Cost-Sensitive Learning.
Int. J. Pattern Recognit. Artif. Intell.
Liangxiao Jiang, Chen Qiu, Chaoqun Li
2015 B conf
A differential evolution-based method for class-imbalanced cost-sensitive learning.
IJCNN
Chen Qiu, Liangxiao Jiang, Ganggang Kong
2015 J jnl
Adapting naive Bayes tree for text classification.
Knowl. Inf. Syst.
Shasha Wang, Liangxiao Jiang, Chaoqun Li
2015 J jnl
Not always simple classification: Learning SuperParent for class probability estimation.
Expert Syst. Appl.
Chen Qiu, Liangxiao Jiang, Chaoqun Li
2014 C conf
A CFS-Based Feature Weighting Approach to Naive Bayes Text Classifiers.
ICANN
Shasha Wang, Liangxiao Jiang, Chaoqun Li
2014 J jnl
A Novel Distance Function: frequency difference Metric.
Int. J. Pattern Recognit. Artif. Intell.
Liangxiao Jiang, Chaoqun Li, Harry Zhang, Zhihua Cai
2014 J jnl
Bayesian Citation-KNN with distance weighting.
Int. J. Mach. Learn. Cybern.
Liangxiao Jiang, Zhihua Cai, Dianhong Wang, Harry Zhang
2014 J jnl
Cost-sensitive Bayesian network classifiers.
Pattern Recognit. Lett.
Liangxiao Jiang, Chaoqun Li, Shasha Wang
2014 J jnl
Local value difference metric.
Pattern Recognit. Lett.
Chaoqun Li, Liangxiao Jiang, Hongwei Li
2014 J jnl
Naive Bayes for value difference metric.
Frontiers Comput. Sci.
Chaoqun Li, Liangxiao Jiang, Hongwei Li
2013 J jnl
An Augmented Value Difference Measure.
Pattern Recognit. Lett.
Liangxiao Jiang, Chaoqun Li
2013 B conf
Attribute Weighted Value Difference Metric.
ICTAI
Chaoqun Li, Liangxiao Jiang, Hongwei Li, Shasha Wang
2013 J jnl
Finding time series discord based on bit representation clustering.
Knowl. Based Syst.
Guiling Li, Olli Bräysy, Liangxiao Jiang, Zongda Wu, Yuanzhen Wang
2013 J jnl
Naive Bayes text classifiers: a locally weighted learning approach.
J. Exp. Theor. Artif. Intell.
Liangxiao Jiang, Zhihua Cai, Harry Zhang, Dianhong Wang
2013 B conf
Sampled Bayesian Network Classifiers for Class-Imbalance and Cost-Sensitive Learning.
ICTAI
Liangxiao Jiang, Chaoqun Li, Zhihua Cai, Harry Zhang
2012 J jnl
Discriminatively Weighted Naive Bayes and its Application in Text Classification.
Int. J. Artif. Intell. Tools
Liangxiao Jiang, Dianhong Wang, Zhihua Cai
2012 J jnl
Improving Tree augmented Naive Bayes for class probability estimation.
Knowl. Based Syst.
Liangxiao Jiang, Zhihua Cai, Dianhong Wang, Harry Zhang
2012 J jnl
Learning Instance Weighted Naive Bayes from labeled and unlabeled data.
J. Intell. Inf. Syst.
Liangxiao Jiang
2012 J jnl
Not so greedy: Randomly Selected Naive Bayes.
Expert Syst. Appl.
Liangxiao Jiang, Zhihua Cai, Harry Zhang, Dianhong Wang
2012 J jnl
Rough Set Approach to Multivariate Decision Trees Inducing.
J. Comput.
Dianhong Wang, Xingwen Liu, Liangxiao Jiang, Xiaoting Zhang, Yongguang Zhao
2012 J jnl
Weighted average of one-dependence estimators†.
J. Exp. Theor. Artif. Intell.
Liangxiao Jiang, Harry Zhang, Zhihua Cai, Dianhong Wang
2011 Misc conf
A novel method for inducing ID3 decision trees based on variable precision rough set.
ICNC
Xingwen Liu, Dianhong Wang, Liangxiao Jiang, Fenxiong Chen, Shengfeng Gan
2011 J jnl
An Empirical Study on Class Probability Estimates in Decision Tree Learning.
J. Softw.
Liangxiao Jiang, Chaoqun Li
2011 J jnl
Learning random forests for ranking.
Frontiers Comput. Sci. China
Liangxiao Jiang
2011 J jnl
Random one-dependence estimators.
Pattern Recognit. Lett.
Liangxiao Jiang
2011 J jnl
Scaling Up the Accuracy of Decision-Tree Classifiers: A Naive-Bayes Combination.
J. Comput.
Liangxiao Jiang, Chaoqun Li
2009 J jnl
A Novel Bayes Model: Hidden Naive Bayes.
IEEE Trans. Knowl. Data Eng.
Liangxiao Jiang, Harry Zhang, Zhihua Cai
2009 J jnl
Decision Tree with Better Class Probability Estimation.
Int. J. Pattern Recognit. Artif. Intell.
Liangxiao Jiang, Chaoqun Li, Zhihua Cai
2009 J jnl
Learning decision tree for ranking.
Knowl. Inf. Syst.
Liangxiao Jiang, Chaoqun Li, Zhihua Cai
2008 — conf
A Combined Classification Algorithm Based on C4.5 and NB.
ISICA
Liangxiao Jiang, Chaoqun Li, Jia Wu, Jian Zhu
2008 J jnl
Enhancing the performance of differential evolution using orthogonal design method.
Appl. Math. Comput.
Wenyin Gong, Zhihua Cai, Liangxiao Jiang
2008 J jnl
Using Instance cloning to Improve Naive Bayes for Ranking.
Int. J. Pattern Recognit. Artif. Intell.
Liangxiao Jiang, Dianhong Wang, Harry Zhang, Zhihua Cai, Bo Huang
2007 — conf
An Improved Attribute Selection Measure for Decision Tree Induction.
FSKD (4)
Dianhong Wang, Liangxiao Jiang
2007 — conf
K-Distributions: A New Algorithm for Clustering Categorical Data.
ICIC (2)
Zhihua Cai, Dianhong Wang, Liangxiao Jiang
2007 B conf
Learning Locally Weighted C4.4 for Class Probability Estimation.
Discovery Science
Liangxiao Jiang, Harry Zhang, Dianhong Wang, Zhihua Cai
2007 — conf
Scaling Up the Accuracy of Bayesian Network Classifiers by M-Estimate.
ICIC (2)
Liangxiao Jiang, Dianhong Wang, Zhihua Cai
2007 — conf
Survey of Improving K-Nearest-Neighbor for Classification.
FSKD (1)
Liangxiao Jiang, Zhihua Cai, Dianhong Wang, Siwei Jiang
2007 C conf
Survey of Improving Naive Bayes for Classification.
ADMA
Liangxiao Jiang, Dianhong Wang, Zhihua Cai, Xuesong Yan
2006 — conf
A Novel One-dependence Estimator Based on Multi-parents.
ISDA (1)
Dan Zeng, Sifa Zhang, Zhihua Cai, Siwei Jiang, Liangxiao Jiang
2006 — conf
Augmented Naive Bayes Based on Evolutional Strategy.
ISDA (1)
Dan Zeng, Sifa Zhang, Zhihua Cai, Siwei Jiang, Liangxiao Jiang
2006 — conf
Dynamic K-Nearest-Neighbor Naive Bayes with Attribute Weighted.
FSKD
Liangxiao Jiang, Harry Zhang, Zhihua Cai
2006 — conf
Lazy Averaged One-Dependence Estimators.
Canadian AI
Liangxiao Jiang, Harry Zhang
2006 — conf
Learning Naive Bayes for Probability Estimation by Feature Selection.
Canadian AI
Liangxiao Jiang, Harry Zhang
2006 B conf
Using Locally Weighted Learning to Improve SMOreg for Regression.
PRICAI
Chaoqun Li, Liangxiao Jiang
2006 B conf
Weightily Averaged One-Dependence Estimators.
PRICAI
Liangxiao Jiang, Harry Zhang
2005 A* conf
Augmenting naive Bayes for ranking.
ICML
Harry Zhang, Liangxiao Jiang, Jiang Su
2005 A* conf
Hidden Naive Bayes.
AAAI
Harry Zhang, Liangxiao Jiang, Jiang Su
2005 — conf
Instance Cloning Local Naive Bayes.
Canadian AI
Liangxiao Jiang, Harry Zhang, Jiang Su
2005 C conf
Learning
ADMA
Liangxiao Jiang, Harry Zhang, Jiang Su
2005 A* conf
Learning Instance Greedily Cloning Naive Bayes for Ranking.
ICDM
Liangxiao Jiang, Harry Zhang
2005 B conf
Learning Lazy Naive Bayesian Classifiers for Ranking.
ICTAI
Liangxiao Jiang, Yuanyuan Guo
2005 B conf
Learning Tree Augmented Naive Bayes for Ranking.
DASFAA
Liangxiao Jiang, Harry Zhang, Zhihua Cai, Jiang Su
2005 C conf
One Dependence Augmented Naive Bayes.
ADMA
Liangxiao Jiang, Harry Zhang, Zhihua Cai, Jiang Su