Results 21 to 30 of about 2,307,608 (312)
Homomorphic Encryption-Based Federated Privacy Preservation for Deep Active Learning
Entropy, 2022 Active learning is a technique for maximizing performance of machine learning with minimal labeling effort and letting the machine automatically and adaptively select the most informative data for labeling.
Hendra Kurniawan, Masahiro Mambo
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Nature Communications, 2023 Porous carbons are the active materials of choice for supercapacitor applications because of their power capability, long-term cycle stability, and wide operating temperatures.
Tao Wang +14 more
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Comparative analysis of machine learning methods for active flow control [PDF]
Journal of Fluid Mechanics, 2022 Machine learning frameworks such as genetic programming and reinforcement learning (RL) are gaining popularity in flow control. This work presents a comparative analysis of the two, benchmarking some of their most representative algorithms against global
F. Pino +3 more
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A Comparative Analysis of Active Learning for Rumor Detection on Social Media Platforms
Applied Sciences, 2023 In recent years, the ubiquity of social networks has transformed them into essential platforms for information dissemination. However, the unmoderated nature of social networks and the advent of advanced machine learning techniques, including generative ...
Feng Yi +3 more
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A Review on Machine Learning Styles in Computer Vision—Techniques and Future Directions
IEEE Access, 2022 Computer applications have considerably shifted from single data processing to machine learning in recent years due to the accessibility and availability of massive volumes of data obtained through the internet and various sources.
Supriya V. Mahadevkar +6 more
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Human Gait Activity Recognition Machine Learning Methods
Sensors, 2023 Human gait activity recognition is an emerging field of motion analysis that can be applied in various application domains. One of the most attractive applications includes monitoring of gait disorder patients, tracking their disease progression and the modification/evaluation of drugs.
Jan Slemenšek +6 more
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Kernel learning for ligand-based virtual screening: discovery of a new PPARgamma agonist [PDF]
, 2010 Poster presentation at 5th German Conference on Cheminformatics: 23. CIC-Workshop Goslar, Germany. 8-10 November 2009 We demonstrate the theoretical and practical application of modern kernel-based machine learning methods to ligand-based virtual ...
Hansen, Katja +9 more
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Learning to Actively Learn Neural Machine Translation [PDF]
Proceedings of the 22nd Conference on Computational Natural Language Learning, 2018 Traditional active learning (AL) methods for machine translation (MT) rely on heuristics. However, these heuristics are limited when the characteristics of the MT problem change due to e.g. the language pair or the amount of the initial bitext. In this paper, we present a framework to learn sentence selection strategies for neural MT.
Ming Liu +2 more
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Enabling robust offline active learning for machine learning potentials using simple physics-based priors [PDF]
Machine Learning: Science and Technology, 2020 Machine learning surrogate models for quantum mechanical simulations have enabled the field to efficiently and accurately study material and molecular systems.
Muhammed Shuaibi +3 more
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Improving molecular machine learning through adaptive subsampling with active learning
Digital Discovery, 2023 Active machine learning can be used to sample training data in an autonomous manner to improve machine learning performance. This approach is competitive with state-of-the-art data sampling approaches, especially on erroneous data.
Yujing Wen +3 more
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