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Parallelizable Stack Long Short-Term Memory [PDF]
Proceedings of the Third Workshop on Structured Prediction for, 2019 Stack Long Short-Term Memory (StackLSTM) is useful for various applications such as parsing and string-to-tree neural machine translation, but it is also known to be notoriously difficult to parallelize for GPU training due to the fact that the computations are dependent on discrete operations.
Ding, Shuoyang, Koehn, Philipp
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Short-term Load Forecasting with Distributed Long Short-Term Memory
2023 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 2023 5 pages, 4 figures, 2023 ISGT ...
Dong, Yi +3 more
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Video Summarization with Long Short-Term Memory [PDF]
, 2016 We propose a novel supervised learning technique for summarizing videos by automatically selecting keyframes or key subshots. Casting the problem as a structured prediction problem on sequential data, our main idea is to use Long Short-Term Memory (LSTM), a special type of recurrent neural networks to model the variable-range dependencies entailed in ...
Zhang, Ke +3 more
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Intrinsically Sparse Long Short-Term Memory Networks
arXiv, 2019 Long Short-Term Memory (LSTM) has achieved state-of-the-art performances on a wide range of tasks. Its outstanding performance is guaranteed by the long-term memory ability which matches the sequential data perfectly and the gating structure controlling the information flow.
Liu, Shiwei +2 more
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Generating image descriptions with multidirectional 2D long short‐term memory
IET Computer Vision, 2017 Connecting visual imagery with descriptive language is a challenge for computer vision and machine translation. To approach this problem, the authors propose a novel end‐to‐end model to generate descriptions for images.
Shuohao Li +4 more
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Dependency-based long short term memory network for drug-drug interaction extraction
BMC Bioinformatics, 2017 Background Drug-drug interaction extraction (DDI) needs assistance from automated methods to address the explosively increasing biomedical texts. In recent years, deep neural network based models have been developed to address such needs and they have ...
Wei Wang +5 more
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The Effects of Regular Pilates Exercise on Long-Term and Short-Term Memory of the Elderly [PDF]
روانشناسی پیری, 2017 In today’s world, the issue of physical and psychological health and well-being of the elderly is one of the most important global concerns. Evidence suggests that physical activity can improve mental and cognitive performance and also play a role in ...
Nayereh Joolaei +2 more
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Location Prediction of Sperm Cells Using Long Short‐Term Memory Networks
Advanced Intelligent Systems, 2023 Intracytoplasmic sperm injection (ICSI) requires precise selection of a single sperm cell in a dish to be injected into an oocyte. This task is challenging due to high sperm velocity, collision with other sperm cells, and changes in the imaging focus ...
Lioz Noy +5 more
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Malware Classification using Long Short-term Memory Models
Proceedings of the 7th International Conference on Information Systems Security and Privacy, 2021 Signature and anomaly based techniques are the quintessential approaches to malware detection. However, these techniques have become increasingly ineffective as malware has become more sophisticated and complex. Researchers have therefore turned to deep learning to construct better performing model.
Dang, Dennis +2 more
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