Kui Yu

Orcid: 0000-0003-2442-4572

According to our database1, Kui Yu authored at least 111 papers between 2006 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Progressive Skeleton Learning for Effective Local-to-Global Causal Structure Learning.
IEEE Trans. Knowl. Data Eng., December, 2024

Causal Discovery From Unknown Interventional Datasets Over Overlapping Variable Sets.
IEEE Trans. Knowl. Data Eng., December, 2024

Lgt: long-range graph transformer for early rumor detection.
Soc. Netw. Anal. Min., December, 2024

Adaptive Prototype Interaction Network for Few-Shot Knowledge Graph Completion.
IEEE Trans. Neural Networks Learn. Syst., November, 2024

FDKT: Towards an Interpretable Deep Knowledge Tracing via Fuzzy Reasoning.
ACM Trans. Inf. Syst., September, 2024

Discovering Ancestral Instrumental Variables for Causal Inference From Observational Data.
IEEE Trans. Neural Networks Learn. Syst., August, 2024

Fair Feature Selection: A Causal Perspective.
ACM Trans. Knowl. Discov. Data, August, 2024

Learning Causal Chain Graph Structure via Alternate Learning and Double Pruning.
IEEE Trans. Big Data, August, 2024

Bootstrap-Based Layerwise Refining for Causal Structure Learning.
IEEE Trans. Artif. Intell., June, 2024

Diverse Structure-Aware Relation Representation in Cross-Lingual Entity Alignment.
ACM Trans. Knowl. Discov. Data, May, 2024

Local causal structure learning with missing data.
Expert Syst. Appl., March, 2024

Feature Selection for Efficient Local-to-global Bayesian Network Structure Learning.
ACM Trans. Knowl. Discov. Data, February, 2024

Causal Feature Selection With Dual Correction.
IEEE Trans. Neural Networks Learn. Syst., January, 2024

A cross-network node classification method in open-set scenario.
Pattern Recognit., 2024

Discovering causally invariant features for out-of-distribution generalization.
Pattern Recognit., 2024

Zero-shot learning with visual-semantic mutual reinforcement for image recognition.
J. Electronic Imaging, 2024

Linking Model Intervention to Causal Interpretation in Model Explanation.
CoRR, 2024

Causal Multi-Label Feature Selection in Federated Setting.
CoRR, 2024

Sample Quality Heterogeneity-aware Federated Causal Discovery through Adaptive Variable Space Selection.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Causal Inference with Conditional Front-Door Adjustment and Identifiable Variational Autoencoder.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Learning Robust Rationales for Model Explainability: A Guidance-Based Approach.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

FedCSL: A Scalable and Accurate Approach to Federated Causal Structure Learning.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Towards Privacy-Aware Causal Structure Learning in Federated Setting.
IEEE Trans. Big Data, December, 2023

Independent Relation Representation With Line Graph for Cross-Lingual Entity Alignment.
IEEE Trans. Knowl. Data Eng., November, 2023

A novel data enhancement approach to DAG learning with small data samples.
Appl. Intell., November, 2023

Local Causal Discovery in Multiple Manipulated Datasets.
IEEE Trans. Neural Networks Learn. Syst., October, 2023

Adaptive Skeleton Construction for Accurate DAG Learning.
IEEE Trans. Knowl. Data Eng., October, 2023

Causal Feature Selection in the Presence of Sample Selection Bias.
ACM Trans. Intell. Syst. Technol., October, 2023

Toward Unique and Unbiased Causal Effect Estimation From Data With Hidden Variables.
IEEE Trans. Neural Networks Learn. Syst., September, 2023

A Light Causal Feature Selection Approach to High-Dimensional Data.
IEEE Trans. Knowl. Data Eng., August, 2023

Multilabel Feature Selection: A Local Causal Structure Learning Approach.
IEEE Trans. Neural Networks Learn. Syst., June, 2023

Causal Feature Selection With Efficient Spouses Discovery.
IEEE Trans. Big Data, April, 2023

Learning Causal Representations for Robust Domain Adaptation.
IEEE Trans. Knowl. Data Eng., March, 2023

A Drift-Sensitive Distributed LSTM Method for Short Text Stream Classification.
IEEE Trans. Big Data, February, 2023

Fair Causal Feature Selection.
CoRR, 2023

Causal Effect Estimation with Variational AutoEncoder and the Front Door Criterion.
CoRR, 2023

Knowledge-Enhanced Hierarchical Transformers for Emotion-Cause Pair Extraction.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023

TransD-based Multi-hop Meta Learning for Few-shot Knowledge Graph Completion.
Proceedings of the International Joint Conference on Neural Networks, 2023

Cross-Knowledge Graph Relation Completion for Non-isomorphic Cross-lingual Entity Alignment.
Proceedings of the 29th International DMS Conference on Visualization and Visual Languages, 2023

2022
Causal Feature Selection with Missing Data.
ACM Trans. Knowl. Discov. Data, 2022

PSL: An Algorithm for Partial Bayesian Network Structure Learning.
ACM Trans. Knowl. Discov. Data, 2022

Fuzzy Bayesian Knowledge Tracing.
IEEE Trans. Fuzzy Syst., 2022

Dual-Representation-Based Autoencoder for Domain Adaptation.
IEEE Trans. Cybern., 2022

Towards Efficient Local Causal Structure Learning.
IEEE Trans. Big Data, 2022

Causal learner: A toolbox for causal structure and Markov blanket learning.
Pattern Recognit. Lett., 2022

Learning common and label-specific features for multi-Label classification with correlation information.
Pattern Recognit., 2022

Error-aware Markov blanket learning for causal feature selection.
Inf. Sci., 2022

Sufficient dimension reduction for average causal effect estimation.
Data Min. Knowl. Discov., 2022

Explanatory causal effects for model agnostic explanations.
CoRR, 2022

Learning Relation-Specific Representations for Few-shot Knowledge Graph Completion.
CoRR, 2022

A New Skeleton-Neural DAG Learning Approach.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

Partial Multi-Label Feature Selection.
Proceedings of the International Joint Conference on Neural Networks, 2022

Learning Inter-Entity-Interaction for Few-Shot Knowledge Graph Completion.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Bootstrap-based Causal Structure Learning.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Efficient Causal Structure Learning from Multiple Interventional Datasets with Unknown Targets.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
A Unified View of Causal and Non-causal Feature Selection.
ACM Trans. Knowl. Discov. Data, 2021

Using Feature Selection for Local Causal Structure Learning.
IEEE Trans. Emerg. Top. Comput. Intell., 2021

Learning Cross-Lingual Mappings in Imperfectly Isomorphic Embedding Spaces.
IEEE ACM Trans. Audio Speech Lang. Process., 2021

Semi-supervised classification on data streams with recurring concept drift and concept evolution.
Knowl. Based Syst., 2021

Separation and recovery Markov boundary discovery and its application in EEG-based emotion recognition.
Inf. Sci., 2021

A general framework for causal classification.
Int. J. Data Sci. Anal., 2021

Causality-based Feature Selection: Methods and Evaluations.
ACM Comput. Surv., 2021

Feature Selection for Efficient Local-to-Global Bayesian Network Structure Learning.
CoRR, 2021

Any Part of Bayesian Network Structure Learning.
CoRR, 2021

Adversarial training with Wasserstein distance for learning cross-lingual word embeddings.
Appl. Intell., 2021

Improving Gradient-based DAG Learning by Structural Asymmetry.
Proceedings of the 2021 IEEE International Conference on Big Knowledge, 2021

Accelerating Learning Bayesian Network Structures by Reducing Redundant CI Tests.
Proceedings of the 2021 IEEE International Conference on Big Knowledge, 2021

A Local Similarity-Preserving Framework for Nonlinear Dimensionality Reduction with Neural Networks.
Proceedings of the Database Systems for Advanced Applications, 2021

2020
Learning Markov Blankets From Multiple Interventional Data Sets.
IEEE Trans. Neural Networks Learn. Syst., 2020

Accurate Markov Boundary Discovery for Causal Feature Selection.
IEEE Trans. Cybern., 2020

Multi-Source Causal Feature Selection.
IEEE Trans. Pattern Anal. Mach. Intell., 2020

Towards efficient and effective discovery of Markov blankets for feature selection.
Inf. Sci., 2020

Towards precise causal effect estimation from data with hidden variables.
CoRR, 2020

Markov Boundary Learning With Streaming Data for Supervised Classification.
IEEE Access, 2020

Causal Query in Observational Data with Hidden Variables.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

Multi-Label Causal Feature Selection.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Markov Boundary-Based Outlier Mining.
IEEE Trans. Neural Networks Learn. Syst., 2019

BAMB: A Balanced Markov Blanket Discovery Approach to Feature Selection.
ACM Trans. Intell. Syst. Technol., 2019

Semantic Features Prediction for Pulmonary Nodule Diagnosis Based on Online Streaming Feature Selection.
IEEE Access, 2019

Predicting the Semantic Characteristics of Pulmonary Nodules using Feature Selection Based on Maximum-relevance Minimum-redundancy.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

Joint Semi-Supervised Feature Selection and Classification through Bayesian Approach.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Mining Markov Blankets Without Causal Sufficiency.
IEEE Trans. Neural Networks Learn. Syst., 2018

Streaming feature-based causal structure learning algorithm with symmetrical uncertainty.
Inf. Sci., 2018

Discovering Markov Blanket from Multiple interventional Datasets.
CoRR, 2018

miRBaseConverter: an R/Bioconductor package for converting and retrieving miRNA name, accession, sequence and family information in different versions of miRBase.
BMC Bioinform., 2018

Galaxy: Towards Scalable and Interpretable Explanation on High-Dimensional and Spatio-Temporal Correlated Climate Data.
Proceedings of the 2018 IEEE International Conference on Big Knowledge, 2018

TL-PC: An Interpretable Causal Relationship Networks on Older Adults Fall Influence Factors.
Proceedings of the 2018 IEEE International Conference on Big Knowledge, 2018

2017
Markov Blanket Feature Selection Using Representative Sets.
IEEE Trans. Neural Networks Learn. Syst., 2017

2016
Scalable and Accurate Online Feature Selection for Big Data.
ACM Trans. Knowl. Discov. Data, 2016

LOFS: A library of online streaming feature selection.
Knowl. Based Syst., 2016

An evaluation of big data analytics in feature selection for long-lead extreme floods forecasting.
Proceedings of the 13th IEEE International Conference on Networking, Sensing, and Control, 2016

A Novel Android Malware Detection Method Based on Markov Blanket.
Proceedings of the IEEE First International Conference on Data Science in Cyberspace, 2016

2015
Classification with Streaming Features: An Emerging-Pattern Mining Approach.
ACM Trans. Knowl. Discov. Data, 2015

Tornado Forecasting with Multiple Markov Boundaries.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

2014
Towards Scalable and Accurate Online Feature Selection for Big Data.
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

2013
Bridging Causal Relevance and Pattern Discriminability: Mining Emerging Patterns from High-Dimensional Data.
IEEE Trans. Knowl. Data Eng., 2013

Online Feature Selection with Streaming Features.
IEEE Trans. Pattern Anal. Mach. Intell., 2013

Towards long-lead forecasting of extreme flood events: a data mining framework for precipitation cluster precursors identification.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

Markov Blanket Feature Selection with Non-faithful Data Distributions.
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

2012
Exploring Causal Relationships with Streaming Features.
Comput. J., 2012

Mining emerging patterns by streaming feature selection.
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Alliance Mechanism Based on Cloud Computing.
Proceedings of the Information Computing and Applications - Third International Conference, 2012

2011
L1 regularized ordering for learning Bayesian network classifiers.
Proceedings of the Seventh International Conference on Natural Computation, 2011

Causal Associative Classification.
Proceedings of the 11th IEEE International Conference on Data Mining, 2011

2010
Online Streaming Feature Selection.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Causal Discovery from Streaming Features.
Proceedings of the ICDM 2010, 2010

Application of the multi-level fuzzy decision-making method in the social evaluation of hydraulic engineering construction project.
Proceedings of the Third International Workshop on Advanced Computational Intelligence, 2010

Online causal discovery.
Proceedings of the 9th IEEE International Conference on Cognitive Informatics, 2010

2009
Application of Fuzzy Dynamic Programming Model in the Coordination Analysis and Allocation of Regional Water Resources.
Proceedings of the 2009 Second International Symposium on Computational Intelligence and Design, 2009

2007
A Parallel Algorithm for Learning Bayesian Networks.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2007

2006
Triangulation of Bayesian Networks Using an Adaptive Genetic Algorithm.
Proceedings of the Foundations of Intelligent Systems, 16th International Symposium, 2006


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