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Advances-in-Partial-Label-Learning

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A list of awesome partial-label learning papers and codes.

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# Advances-in-Partial-Label-Learning

A list of awesome partial-label learning papers and codes.

> **This repository will not be updated since Dec 2023.**

#### Related repository
* [Learning with noisy labels](https://github.com/weijiaheng/Advances-in-Label-Noise-Learning)
* [Learning with Partial Labels/Complementary Labels](https://github.com/wu-dd/Advances-in-Partial-and-Complementary-Label-Learning)

#### Related project
* Southeast University PALM Lab [[Data]](http://palm.seu.edu.cn/zhangml/Resources.htm#data) [[Code]](http://palm.seu.edu.cn/zhangml/Resources.htm#codes)
 
#### If you have any problems or suggestions about this repository, please contact 1998v7@gmail.com.

### Papers & Code in 2023
-----
* [ICCV 2023] Learning in Imperfect Environment: Multi-Label Classification with Long-Tailed Distribution and Partial Labels. [[Paper]](https://arxiv.org/pdf/2304.10539.pdf)
* [ICCV 2023] Candidate-aware Selective Disambiguation Based On Normalized Entropy for Instance-dependent Partial-label Learning. [[Paper]](https://openaccess.thecvf.com/content/ICCV2023/papers/He_Candidate-aware_Selective_Disambiguation_Based_On_Normalized_Entropy_for_Instance-dependent_Partial-label_ICCV_2023_paper.pdf)
* [CVPR 2023] Towards Effective Visual Representations for Partial-Label Learning. [[Paper]](https://arxiv.org/abs/2305.06080)
* [CVPR 2023] Bridging the Gap between Model Explanations in Partially Annotated Multi-label Classification. [[Paper]](https://arxiv.org/abs/2304.01804)
* [ICML 2023] Revisiting Pseudo-Label for Single-Positive Multi-Label Learning. [[Paper]](https://proceedings.mlr.press/v202/liu23ar/liu23ar.pdf)
* [IJCAI 2023] Deep Partial Multi-Label Learning with Graph Disambiguation. [[Paper]](https://www.ijcai.org/proceedings/2023/0479.pdf)
* [IJCAI 2023] Unreliable Partial Label Learning with Recursive Separation. [[Paper]](https://arxiv.org/abs/2302.09891)
* [ICLR 2023] Partial Label Unsupervised Domain Adaptation with Class-Prototype Alignment. [[Paper]](https://openreview.net/forum?id=jpq0qHggw3t)
* [ICLR 2023] Mutual Partial Label Learning with Competitive Label Noise. [[Paper]](https://openreview.net/forum?id=EUrxG8IBCrC)
* [ICLR 2023] Long-Tailed Partial Label Learning via Dynamic Rebalancing. [[Paper]](https://openreview.net/forum?id=sXfWoK4KvSW)
* [ICLR 2023] Decompositional Generation Process for Instance-Dependent Partial Label Learning. [[Paper]](https://openreview.net/forum?id=lKOfilXucGB)
* [AAAI 2023] Can Label-Specific Features Help Partial-Label Learning?. [[Paper]](http://palm.seu.edu.cn/zhangml/files/AAAI'23a.pdf)
* [AAAI 2023] Partial-Label Regression. [[Paper]](https://personal.ntu.edu.sg/boan/papers/AAAI23-PLR.pdf)
* [AAAI 2023] Learning with Partial Labels from Semi-supervised Perspective. [[Paper]](https://arxiv.org/abs/2211.13655)

### Papers & Code in 2022
-----

* [ICML 2022] Revisiting Consistency Regularization for Deep Partial Label Learning. [[Paper]](https://proceedings.mlr.press/v162/wu22l.html)
* [ICML 2022] Partial Label Learning via Label Influence Function. [[Paper]](https://proceedings.mlr.press/v162/gong22c.html)
* [IJCAI 2022] Ambiguity-Induced Contrastive Learning for Instance-Dependent Partial Label Learning. [[Paper]](https://www.ijcai.org/proceedings/2022/0502.pdf) [[Code]](https://github.com/AlphaXia/ABLE)
* [IJCAI 2022] Exploring Binary Classifcation Hidden within Partial Label Learning [[Paper]](https://www.ijcai.org/proceedings/2022/0456.pdf)
* [IJCAI 2022] Deep Graph Matching for Partial Label Learning [[Paper]](https://www.ijcai.org/proceedings/2022/0459.pdf)
* [IJCAI 2022] Webly-Supervised Fine-Grained Recognition with Partial Label Learning [[Paper]](https://www.ijcai.org/proceedings/2022/0209.pdf)
* [CVPR 2022] Multi-Label Classification With Partial Annotations Using Class-Aware Selective Loss. [[Paper]](https://arxiv.org/abs/2110.10955) [[Code]](https://github.com/alibaba-miil/partiallabelingcsl)
* [AAAI 2022] Structured Semantic Transfer for Multi-Label Recognition with Partial Labels. [[Paper]](https://arxiv.org/abs/2112.10941) [[Code]](https://github.com/hcplab-sysu/hcp-mlr-pl)
* [AAAI 2022] Semantic-Aware Representation Blending for Multi-Label Image Recognition with Partial Labels. [[Paper]](https://arxiv.org/abs/2203.02172) [[Code]](https://github.com/hcplab-sysu/hcp-mlr-pl)
* [AAAI 2022] Partial Multi-Label Learning via Large Margin Nearest Neighbour Embeddings. [[Paper]](https://ojs.aaai.org/index.php/AAAI/article/view/20628)
* [ICLR 2022] PiCO: Contrastive Label Disambiguation for Partial Label Learning. [[Paper]](https://openreview.net/pdf?id=EhYjZy6e1gJ) [[Code]](https://github.com/hbzju/pico)
* [ICLR 2022] Exploiting Class Activation Value for Partial-Label Learning. [[Paper]](https://openreview.net/forum?id=qqdXHUGec9h)
* [AISTATS 2022] Learning from Multiple Noisy Partial Labelers. [[Paper]](https://arxiv.org/pdf/2106.04530v2.pdf) [[Code]](https://github.com/batsresearch/nplm)
* [KDD 2022] Partial-Label Learning with Semantic Label Representations. [[Paper]](https://dl.acm.org/doi/abs/10.1145/3534678.3539434)
* [TPAMI 2022] Adaptive graph guided disambiguation for partial label learning. [[Paper]](http://palm.seu.edu.cn/zhangml/files/TPAMI'21b.pdf)
* [TKDD 2022] Disambiguation enabled linear discriminant analysis for partial label dimensionality reduction. [[Paper]](http://palm.seu.edu.cn/zhangml/files/TKDD'21b.pdf)

### Papers & Code in 2021
-----
* [NIPS 2021] Instance-Dependent Partial Label Learning. [[Paper]](https://arxiv.org/pdf/2110.12911v2.pdf) [[Code]](https://github.com/palm-ml/valen)
* [NIPS 2021] Understanding Partial Multi-Label Learning via Mutual Information. [[Paper]](https://arxiv.org/pdf/2110.12911v2.pdf)
* [IJCAI 2021] Few-Shot Partial-Label Learning. [[Paper]](https://arxiv.org/pdf/2106.00984v1.pdf)
* [IJCAI 2021] Multi-level Generative Models for Partial Label Learning with Non-random Label Noise. [[Paper]](https://arxiv.org/pdf/2005.05407v1.pdf)
* [IJCAI 2021] Partial Multi-Label Optimal Margin Distribution Machine. [[Paper]](https://www.ijcai.org/proceedings/2021/0303.pdf)
* [ICML 2021] Leveraged Weighted Loss for Partial Label Learning. [[Paper]](https://arxiv.org/pdf/2106.05731v1.pdf) [[Code]](https://github.com/hongwei-wen/LW-loss-for-partial-label)
* [AAAI 2021] Exploiting Unlabeled Data via Partial Label Assignment for Multi-Class Semi-Supervised Learning. [[Paper]](https://ojs.aaai.org/index.php/AAAI/article/view/17310)
* [ICLR 2021] Towards Impartial Multi-task Learning. [[Paper]](https://openreview.net/forum?id=IMPnRXEWpvr) [[Code]](https://github.com/avivnavon/nash-mtl)

### Papers & Code in 2020
-----
* [NIPS 2020] Semi-Supervised Partial Label Learning via Confidence-Rated Margin Maximization. [[Paper]](https://papers.nips.cc/paper/2020/file/4dea382d82666332fb564f2e711cbc71-Paper.pdf)
* [NIPS 2020] Provably Consistent Partial-Label Learning. [[Paper]](https://papers.nips.cc/paper/2020/file/7bd28f15a49d5e5848d6ec70e584e625-Paper.pdf)
* [IJCAI 2020] Learning From Multi-Dimensional Partial Labels. [[Paper]](https://www.ijcai.org/Proceedings/2020/0407.pdf)
* [IJCAI 2020] Partial Multi-Label Learning via Multi-Subspace Representation. [[Paper]](https://www.ijcai.org/proceedings/2020/0362.pdf)
* [ICML 2020] Progressive Identification of True Labels for Partial-Label Learning. [[Paper]](https://arxiv.org/pdf/2002.08053v3.pdf) [[Code]](https://github.com/Lvcrezia77/PRODEN)
* [AAAI 2020] General Partial Label Learning via Dual Bipartite Graph Autoencoder. [[Paper]](https://arxiv.org/pdf/2001.01290.pdf)
* [AAAI 2020][TPAMI] Partial Multi-label Learning with Noisy Label Identification. [[Paper]](https://ojs.aaai.org/index.php/AAAI/article/view/6117)
* [AAAI 2020] Partial Multi-Label Learning with Label Distribution. [[Paper]](https://ojs.aaai.org/index.php/AAAI/article/view/6124)
* [AAAI 2020] Multi-View Partial Multi-Label Learning with Graph-Based Disambiguation. [[Paper]](https://ojs.aaai.org/index.php/AAAI/article/view/5761)
* [AAAI 2020] Partial Label Learning with Batch Label Correction. [[Paper]](https://ojs.aaai.org/index.php/AAAI/article/view/6132)
* [CVPR 2020] Interactive Multi-Label CNN Learning with Partial Labels. [[Paper]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Huynh_Interactive_Multi-Label_CNN_Learning_With_Partial_Labels_CVPR_2020_paper.pdf)

### Papers & Code before 2020
----
* [AAAI 2019] Partial Label Learning with Self-Guided Retraining. [[Paper]](https://ojs.aaai.org/index.php/AAAI/article/view/4233)
* [AAAI 2019] Partial Label Learning via Label Enhancement. [[Paper]](https://ojs.aaai.org/index.php/AAAI/article/view/4497)
* [IJCAI 2019] Partial Label Learning with Unlabeled Data. [[Paper]](https://www.ijcai.org/Proceedings/2019/0521.pdf)
* [IJCAI 2019] Partial Label Learning by Semantic Difference Maximization. [[Paper]](https://www.ijcai.org/proceedings/2019/0318.pdf)

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