Results 41 to 50 of about 12,744 (261)
Weakly Supervised Representation Learning with Sparse Perturbations
Advances in Neural Information Processing Systems 35, 2022 The theory of representation learning aims to build methods that provably invert the data generating process with minimal domain knowledge or any source of supervision. Most prior approaches require strong distributional assumptions on the latent variables and weak supervision (auxiliary information such as timestamps) to provide provable ...
Ahuja, Kartik +2 more
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From Weakly Supervised Learning to Active Learning
CoRR, 2022 Applied mathematics and machine computations have raised a lot of hope since the recent success of supervised learning. Many practitioners in industries have been trying to switch from their old paradigms to machine learning. Interestingly, those data scientists spend more time scrapping, annotating and cleaning data than fine-tuning models.
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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. audio and visual information representing the lips movements, in a weakly supervised way using Siamese networks and ...
Chaabouni, Rahma +3 more
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Addressing Imbalance in Weakly Supervised Multi-Label Learning
IEEE Access, 2019 Multi-label learning has been widely used in many fields to solve the problem of assigning multiple related categories to an instance. Nevertheless, the label for each training example is assumed complete in most of the current multi-label learning ...
Fang-Fang Luo +2 more
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Medical image segmentation using deep learning: A survey
IET Image Processing, 2022 Deep learning has been widely used for medical image segmentation and a large number of papers has been presented recording the success of deep learning in the field.
Risheng Wang +5 more
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Array, 2023 Due to the emergence of social networking sites and social media platforms, there is faster information dissemination to the public. Unverified information is widely disseminated across social media platforms without any apprehension about the accuracy ...
Liyakathunisa Syed +3 more
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SensorsHuman activity recognition (HAR) using wearable sensors has advanced through various machine learning paradigms, each with inherent trade-offs between performance and labeling requirements.
Taoran Sheng, Manfred Huber
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Instance-Aware Plant Disease Detection by Utilizing Saliency Map and Self-Supervised Pre-Training
Agriculture, 2022 Plant disease detection is essential for optimizing agricultural productivity and crop quality. With the recent advent of deep learning and large-scale plant disease datasets, many studies have shown high performance of supervised learning-based plant ...
Taejoo Kim +3 more
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Unified Risk Analysis for Weakly Supervised Learning
Trans. Mach. Learn. Res., 2023 Among the flourishing research of weakly supervised learning (WSL), we recognize the lack of a unified interpretation of the mechanism behind the weakly supervised scenarios, let alone a systematic treatment of the risk rewrite problem, a crucial step in the empirical risk minimization approach.
Chao-Kai Chiang, Masashi Sugiyama
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Weakly supervised learning of semantic colour terms
IET Computer Vision, 2014 Recognition of visual attributes in images allows an image's information content to be expressed textually. This has benefits for web search and image archiving, especially since visual attributes transcend language barriers.
David Hanwell, Majid Mirmehdi
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