Results 41 to 50 of about 14,201 (266)
Multi-Modal 3D Shape Clustering with Dual Contrastive Learning
Applied Sciences, 2022 3D shape clustering is developing into an important research subject with the wide applications of 3D shapes in computer vision and multimedia fields. Since 3D shapes generally take on various modalities, how to comprehensively exploit the multi-modal ...
Guoting Lin +4 more
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Contrastive Learning for Fair Representations
CoRR, 2021 Trained classification models can unintentionally lead to biased representations and predictions, which can reinforce societal preconceptions and stereotypes. Existing debiasing methods for classification models, such as adversarial training, are often expensive to train and difficult to optimise.
Aili Shen +4 more
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Supervised contrastive learning for recommendation
Knowledge-Based Systems, 2022 In this work, we aim to consider the application of contrastive learning in the scenario of the recommendation system adequately, making it more suitable for recommendation task. We propose a learning paradigm called supervised contrastive learning(SCL) to support the graph convolutional neural network.
Chun Yang +4 more
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Self-Supervised Sequence Recommendation Method Based on Random Self-Attention and Momentum Contrastive Learning [PDF]
Jisuanji gongchengSequence recommendation utilizes user historical sequence behavior to model user interests and provide content recommendations, and is commonly employed in sectors such as news, advertising, and e-commerce.
YU Zhengtao, SUN Ziqin, ZHANG Yongbing, GAO Shengxiang, HUANG Yuxin, TAN Kaiwen
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Frontiers in Physics, 2023 An improved algorithm has been proposed to address the challenges encountered in object detection using visible and thermal infrared images. These challenges include the diversity of object detection perspectives, deformation of the object, occlusion ...
Xiaoguang Tu +7 more
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Faithful Contrastive Features in Learning [PDF]
Cognitive Science, 2006 AbstractThis article pursues the idea of inferring aspects of phonological underlying forms directly from surface contrasts by looking at optimality theoretic linguistic systems (Prince & Smolensky, 1993/2004). The main result proves that linguistic systems satisfying certain conditions have the faithful contrastive feature property: Whenever 2 ...
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Unbiased Supervised Contrastive Learning
CoRR, 2022 Accepted at ICLR 2023 (v3); Fix typo in Eq.19 (v4)
Carlo Alberto Barbano +4 more
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MathematicsGraph contrastive learning has demonstrated significant superiority for collaborative filtering. These methods typically use augmentation technology to generate contrastive views, and then train graph neural networks with contrastive learning as an ...
Jifeng Dong +5 more
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SSCLNet: A Self-Supervised Contrastive Loss-Based Pre-Trained Network for Brain MRI Classification
IEEE Access, 2023 Brain magnetic resonance images (MRI) convey vital information for making diagnostic decisions and are widely used to detect brain tumors. This research proposes a self-supervised pre-training method based on feature representation learning through ...
Animesh Mishra +2 more
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