Weakly supervised machine learning
CAAI Transactions on Intelligence Technology, 2023 Supervised learning aims to build a function or model that seeks as many mappings as possible between the training data and outputs, where each training data will predict as a label to match its corresponding ground‐truth value.
Zeyu Ren, Shuihua Wang, Yudong Zhang
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Weakly-supervised learning of visual relations [PDF]
2017 IEEE International Conference on Computer Vision (ICCV), 2017 This paper introduces a novel approach for modeling visual relations between pairs of objects. We call relation a triplet of the form (subject, predicate, object) where the predicate is typically a preposition (eg.
Laptev, Ivan +3 more
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Weakly-supervised Dictionary Learning
IEEE Transactions on Signal Processing, 2018 We present a probabilistic modeling and inference framework for discriminative analysis dictionary learning under a weak supervision setting. Dictionary learning approaches have been widely used for tasks such as low-level signal denoising and ...
Fern, Xiaoli Z. +3 more
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Learning weakly supervised multimodal phoneme embeddings [PDF]
Interspeech 2017, 2017 Recent works have explored deep architectures for learning multimodal speech representation (e.g. audio and images, articulation and audio) in a supervised way. Here we investigate the role of combining different speech modalities, i.e.
Chaabouni, Rahma +3 more
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A Semi-Automatic Magnetic Resonance Imaging Annotation Algorithm Based on Semi-Weakly Supervised Learning [PDF]
SensorsThe annotation of magnetic resonance imaging (MRI) images plays an important role in deep learning-based MRI segmentation tasks. Semi-automatic annotation algorithms are helpful for improving the efficiency and reducing the difficulty of MRI image ...
Shaolong Chen, Zhiyong Zhang
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Weakly supervised learning for classification of lung cytological images using attention-based multiple instance learning [PDF]
Scientific Reports, 2021 In cytological examination, suspicious cells are evaluated regarding malignancy and cancer type. To assist this, we previously proposed an automated method based on supervised learning that classifies cells in lung cytological images as benign or ...
Atsushi Teramoto +7 more
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SentiUrdu-1M: A large-scale tweet dataset for Urdu text sentiment analysis using weakly supervised learning [PDF]
PLoS ONE, 2023 Low-resource languages are gaining much-needed attention with the advent of deep learning models and pre-trained word embedding. Though spoken by more than 230 million people worldwide, Urdu is one such low-resource language that has recently gained ...
Abdul Ghafoor +5 more
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Accurate prediction of disease-free and overall survival in non-small cell lung cancer using patient-level multimodal weakly supervised learning. [PDF]
NPJ Precis OncolLi Y +10 more
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Weakly Supervised Contrastive Learning [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 Unsupervised visual representation learning has gained much attention from the computer vision community because of the recent achievement of contrastive learning. Most of the existing contrastive learning frameworks adopt the instance discrimination as the pretext task, which treating every single instance as a different class.
Zheng, Mingkai +6 more
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Development of metastasis and survival prediction model of luminal and non-luminal breast cancer with weakly supervised learning based on pathomics. [PDF]
PeerJLiu H, Ying L, Song X, Xiang X, Wei S.
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