193 related articles for article (PubMed ID: 32813649)
1. Incomplete Label Multiple Instance Multiple Label Learning.
Nguyen T; Raich R
IEEE Trans Pattern Anal Mach Intell; 2022 Mar; 44(3):1320-1337. PubMed ID: 32813649
[TBL] [Abstract][Full Text] [Related]
2. Dynamic Programming for Instance Annotation in Multi-Instance Multi-Label Learning.
Pham AT; Raich R; Fern XZ
IEEE Trans Pattern Anal Mach Intell; 2017 Dec; 39(12):2381-2394. PubMed ID: 28103189
[TBL] [Abstract][Full Text] [Related]
3. Learning From Weakly Labeled Data Based on Manifold Regularized Sparse Model.
Zhang J; Li S; Jiang M; Tan KC
IEEE Trans Cybern; 2022 May; 52(5):3841-3854. PubMed ID: 32877346
[TBL] [Abstract][Full Text] [Related]
4. A Concise Yet Effective Model for Non-Aligned Incomplete Multi-View and Missing Multi-Label Learning.
Li X; Chen S
IEEE Trans Pattern Anal Mach Intell; 2022 Oct; 44(10):5918-5932. PubMed ID: 34097605
[TBL] [Abstract][Full Text] [Related]
5. Weakly supervised instance learning for thyroid malignancy prediction from whole slide cytopathology images.
Dov D; Kovalsky SZ; Assaad S; Cohen J; Range DE; Pendse AA; Henao R; Carin L
Med Image Anal; 2021 Jan; 67():101814. PubMed ID: 33049578
[TBL] [Abstract][Full Text] [Related]
6. Sparse Markov chain-based semi-supervised multi-instance multi-label method for protein function prediction.
Han C; Chen J; Wu Q; Mu S; Min H
J Bioinform Comput Biol; 2015 Oct; 13(5):1543001. PubMed ID: 26493682
[TBL] [Abstract][Full Text] [Related]
7. Robust and Discriminative Labeling for Multi-Label Active Learning Based on Maximum Correntropy Criterion.
Du B; Wang Z; Zhang L; Zhang L; Tao D
IEEE Trans Image Process; 2017 Apr; 26(4):1694-1707. PubMed ID: 28092540
[TBL] [Abstract][Full Text] [Related]
8. Centroid Estimation With Guaranteed Efficiency: A General Framework for Weakly Supervised Learning.
Gong C; Yang J; You J; Sugiyama M
IEEE Trans Pattern Anal Mach Intell; 2022 Jun; 44(6):2841-2855. PubMed ID: 33320809
[TBL] [Abstract][Full Text] [Related]
9. A Transfer Learning-Based Multi-Instance Learning Method With Weak Labels.
Xiao Y; Liang F; Liu B
IEEE Trans Cybern; 2022 Jan; 52(1):287-300. PubMed ID: 32149707
[TBL] [Abstract][Full Text] [Related]
10. Towards Safe Weakly Supervised Learning.
Li YF; Guo LZ; Zhou ZH
IEEE Trans Pattern Anal Mach Intell; 2021 Jan; 43(1):334-346. PubMed ID: 31199253
[TBL] [Abstract][Full Text] [Related]
11. LLP-GAN: A GAN-Based Algorithm for Learning From Label Proportions.
Liu J; Wang B; Hang H; Wang H; Qi Z; Tian Y; Shi Y
IEEE Trans Neural Netw Learn Syst; 2023 Nov; 34(11):8377-8388. PubMed ID: 35188896
[TBL] [Abstract][Full Text] [Related]
12. Semi-supervised learning of Hidden Markov Models for biological sequence analysis.
Tamposis IA; Tsirigos KD; Theodoropoulou MC; Kontou PI; Bagos PG
Bioinformatics; 2019 Jul; 35(13):2208-2215. PubMed ID: 30445435
[TBL] [Abstract][Full Text] [Related]
13. UD-MIL: Uncertainty-Driven Deep Multiple Instance Learning for OCT Image Classification.
Wang X; Tang F; Chen H; Luo L; Tang Z; Ran AR; Cheung CY; Heng PA
IEEE J Biomed Health Inform; 2020 Dec; 24(12):3431-3442. PubMed ID: 32248132
[TBL] [Abstract][Full Text] [Related]
14. End-to-end novel visual categories learning via auxiliary self-supervision.
Qing Y; Zeng Y; Cao Q; Huang GB
Neural Netw; 2021 Jul; 139():24-32. PubMed ID: 33677376
[TBL] [Abstract][Full Text] [Related]
15. Deep Double Incomplete Multi-View Multi-Label Learning With Incomplete Labels and Missing Views.
Wen J; Liu C; Deng S; Liu Y; Fei L; Yan K; Xu Y
IEEE Trans Neural Netw Learn Syst; 2023 Mar; PP():. PubMed ID: 37030862
[TBL] [Abstract][Full Text] [Related]
16. A Regularization Approach for Instance-Based Superset Label Learning.
Gong C; Liu T; Tang Y; Yang J; Yang J; Tao D
IEEE Trans Cybern; 2018 Mar; 48(3):967-978. PubMed ID: 28252419
[TBL] [Abstract][Full Text] [Related]
17. A Self-Paced Regularization Framework for Partial-Label Learning.
Lyu G; Feng S; Wang T; Lang C
IEEE Trans Cybern; 2022 Feb; 52(2):899-911. PubMed ID: 32452795
[TBL] [Abstract][Full Text] [Related]
18. Computer-aided diagnosis from weak supervision: a benchmarking study.
Kandemir M; Hamprecht FA
Comput Med Imaging Graph; 2015 Jun; 42():44-50. PubMed ID: 25475486
[TBL] [Abstract][Full Text] [Related]
19. Max-Margin Deep Generative Models for (Semi-)Supervised Learning.
Li C; Zhu J; Zhang B
IEEE Trans Pattern Anal Mach Intell; 2018 Nov; 40(11):2762-2775. PubMed ID: 29989965
[TBL] [Abstract][Full Text] [Related]
20. Collaborative learning with corrupted labels.
Wang Y; Huang R; Huang G; Song S; Wu C
Neural Netw; 2020 May; 125():205-213. PubMed ID: 32145649
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
