Sheng-Jun Huang

Mach. Learn., June, 2023

MUS-CDB: Mixed Uncertainty Sampling With Class Distribution Balancing for Active Annotation in Aerial Object Detection.

[BibT_eX]

[DOI]

IEEE Trans. Geosci. Remote. Sens., 2023

CCMN: A General Framework for Learning With Class-Conditional Multi-Label Noise.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2023

Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

ALL-E: Aesthetics-guided Low-light Image Enhancement.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Improving Lens Flare Removal with General-Purpose Pipeline and Multiple Light Sources Recovery.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Multi-Label Knowledge Distillation.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Implicit Stochastic Gradient Descent for Training Physics-Informed Neural Networks.

[BibT_eX]

[DOI]

Ye Li

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Partial Multi-Label Learning With Noisy Label Identification.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Improving deep label noise learning with dual active label correction.

[BibT_eX]

[DOI]

Mach. Learn., 2022

MUS-CDB: Mixed Uncertainty Sampling with Class Distribution Balancing for Active Annotation in Aerial Object Detection.

[BibT_eX]

[DOI]

CoRR, 2022

Noise-Robust Bidirectional Learning with Dynamic Sample Reweighting.

[BibT_eX]

[DOI]

CoRR, 2022

Meta Objective Guided Disambiguation for Partial Label Learning.

[BibT_eX]

[DOI]

Bo-Shi Zou

CoRR, 2022

A Deep Model for Partial Multi-Label Image Classification with Curriculum Based Disambiguation.

[BibT_eX]

[DOI]

Feng Sun

CoRR, 2022

Label-Aware Global Consistency for Multi-Label Learning with Single Positive Labels.

[BibT_eX]

[DOI]

Jiahao Xiao

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Can Adversarial Training Be Manipulated By Non-Robust Features?

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Active Learning for Multiple Target Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Active Learning for Open-set Annotation.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

A Tailored Physics-informed Neural Network Method for Solving Singularly Perturbed Differential Equations.

[BibT_eX]

[DOI]

Yiwen Pang

Ye Li

Proceedings of the 5th International Conference on Algorithms, 2022

2021

Label Distribution Learning with Label Correlations on Local Samples.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2021

Recent Advances in Open Set Recognition: A Survey.

[BibT_eX]

[DOI]

Chuanxing Geng

IEEE Trans. Pattern Anal. Mach. Intell., 2021

PU Active Learning for Recommender Systems.

[BibT_eX]

[DOI]

Neural Process. Lett., 2021

Visual-guided attentive attributes embedding for zero-shot learning.

[BibT_eX]

[DOI]

Neural Networks, 2021

Preface.

[BibT_eX]

[DOI]

Min-Ling Zhang

Mingsheng Long

J. Comput. Sci. Technol., 2021

Co-Imitation Learning without Expert Demonstration.

[BibT_eX]

[DOI]

CoRR, 2021

Provable Defense Against Delusive Poisoning.

[BibT_eX]

[DOI]

CoRR, 2021

Crowdsourcing aggregation with deep Bayesian learning.

[BibT_eX]

[DOI]

Shaoyuan Li

Sci. China Inf. Sci., 2021

Multi-Label Learning with Pairwise Relevance Ordering.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Partial Multi-Label Learning with Meta Disambiguation.

[BibT_eX]

[DOI]

Feng Sun

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Dual Active Learning for Both Model and Data Selection.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Asynchronous Active Learning with Distributed Label Querying.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Weakly Supervised Crowdsourcing Learning Based on Adversarial Consensus.

[BibT_eX]

[DOI]

Meng-Long Wei

Shao-Yuan Li

Proceedings of the International Conference on Computational Science and Computational Intelligence, 2021

Improving Model Robustness by Adaptively Correcting Perturbation Levels with Active Queries.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Querying Representative and Informative Super-Pixels for Filament Segmentation in Bioimages.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2020

Latent correlation embedded discriminative multi-modal data fusion.

[BibT_eX]

[DOI]

Signal Process., 2020

Adaptive feature weighting for robust Lp-norm sparse representation with application to biometric image classification.

[BibT_eX]

[DOI]

Int. J. Mach. Learn. Cybern., 2020

Incremental Multi-Label Learning with Active Queries.

[BibT_eX]

[DOI]

J. Comput. Sci. Technol., 2020

LGSLRR: Towards fusing discriminative ordinal local and global structured low-rank representation for image recognition.

[BibT_eX]

[DOI]

Inf. Sci., 2020

Reinforcement Learning with Supervision from Noisy Demonstrations.

[BibT_eX]

[DOI]

Kun-Peng Ning

CoRR, 2020

Cost-effectively Identifying Causal Effects When Only Response Variable is Observable.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Semi-Supervised Partial Multi-Label Learning.

[BibT_eX]

[DOI]

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Cross-Task and Cross-Model Active Learning with Meta Features.

[BibT_eX]

[DOI]

Guo-Xiang Li

Yao-Feng Tu

Proceedings of the Big Data and Security - Second International Conference, 2020

Active Learning with Query Generation for Cost-Effective Text Classification.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Uncertainty Aware Graph Gaussian Process for Semi-Supervised Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Fast Multi-Instance Multi-Label Learning.

[BibT_eX]

[DOI]

Wei Gao

IEEE Trans. Pattern Anal. Mach. Intell., 2019

ALiPy: Active Learning in Python.

[BibT_eX]

[DOI]

Guo-Xiang Li

CoRR, 2019

Towards Identifying Causal Relation Between Instances and Labels.

[BibT_eX]

[DOI]

Tian-Zuo Wang

Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Learning Class-Conditional GANs with Active Sampling.

[BibT_eX]

[DOI]

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Multi-View Active Learning for Video Recommendation.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Self-Paced Active Learning: Query the Right Thing at the Right Time.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Active Sampling for Open-Set Classification without Initial Annotation.

[BibT_eX]

[DOI]

Zhao-Yang Liu

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Joint Estimation of Multiple Conditional Gaussian Graphical Models.

[BibT_eX]

[DOI]

Feihu Huang

IEEE Trans. Neural Networks Learn. Syst., 2018

WoCE: A framework for Clustering Ensemble by Exploiting the Wisdom of Crowds Theory.

[BibT_eX]

[DOI]

Muhammad Yousefnezhad

Daoqiang Zhang

IEEE Trans. Cybern., 2018

Cross modal similarity learning with active queries.

[BibT_eX]

[DOI]

Pattern Recognit., 2018

Cost-Effective Training of Deep CNNs with Active Model Adaptation.

[BibT_eX]

[DOI]

Jia-Wei Zhao

Zhao-Yang Liu

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Active Feature Acquisition with Supervised Matrix Completion.

[BibT_eX]

[DOI]

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Cost-Effective Active Learning for Hierarchical Multi-Label Classification.

[BibT_eX]

[DOI]

Yifan Yan

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Partial Multi-Label Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Dual Set Multi-Label Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Margin Distribution Logistic Machine.

[BibT_eX]

[DOI]

Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Multi-instance multi-label active learning.

[BibT_eX]

[DOI]

Nengneng Gao

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Cost-Effective Active Learning from Diverse Labelers.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016

Multi-label active learning by model guided distribution matching.

[BibT_eX]

[DOI]

Nengneng Gao

Frontiers Comput. Sci., 2016

Transfer Learning with Active Queries from Source Domain.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

2015

Multi-Label Active Learning: Query Type Matters.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

2014

Genome-Wide Protein Function Prediction through Multi-Instance Multi-Label Learning.

[BibT_eX]

[DOI]

Jian-Sheng Wu

IEEE ACM Trans. Comput. Biol. Bioinform., 2014

Active Learning by Querying Informative and Representative Examples.

[BibT_eX]

[DOI]

Rong Jin

IEEE Trans. Pattern Anal. Mach. Intell., 2014

2013

Fast Multi-Instance Multi-Label Learning.

[BibT_eX]

[DOI]

CoRR, 2013

Active Query Driven by Uncertainty and Diversity for Incremental Multi-label Learning.

[BibT_eX]

[DOI]

Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

2012

Multi-instance multi-label learning.

[BibT_eX]

[DOI]

Artif. Intell., 2012

Multi-label hypothesis reuse.

[BibT_eX]

[DOI]

Yang Yu

Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Multi-Label Learning by Exploiting Label Correlations Locally.

[BibT_eX]

[DOI]