Results 1 to 10 of about 2,212,722 (355)
The Relationship between Short- and Long-Term Memory Is Preserved across the Age Range
Brain Sciences, 2023 Both short- and long-term memories decline with healthy ageing. The aims of the current study were twofold: firstly, to build on previous studies and investigate the presence of a relationship between short- and long-term memories and, secondly, to ...
Giedrė Čepukaitytė +4 more
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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.
Shuoyang Ding, Philipp Koehn
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, 2021 This paper is based on a machine learning project at the Norwegian University of Science and Technology, fall 2020. The project was initiated with a literature review on the latest developments within time-series forecasting methods in the scientific community over the past five years.
Vennerød, Christian Bakke +2 more
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IEEE Transactions on Instrumentation and Measurement, 2022 Data-driven soft sensors have been widely adopted in industrial processes to learn hidden knowledge automatically from process data, then to monitor difficult-to-measure quality variables.
Chun Fai Lui, Yiqi Liu, Min Xie
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Long Short-Term Memory Recurrent Neural Network for Automatic Speech Recognition
IEEE Access, 2022 Automatic speech recognition (ASR) is one of the most demanding tasks in natural language processing owing to its complexity. Recently, deep learning approaches have been deployed for this task and have been proven to outperform traditional machine ...
Jane Ngozi Oruh +2 more
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THE PSYCHOLINGUISTIC BASIS OF THE LINGUISTIC CONCEPTUALIZATION
Revista de Investigaciones Universidad del Quindío, 2022 The object of this article is the methodology of psycholinguistics concerning analyzing concepts. The article's relevance is due to the need to apply new approaches to linguistic phenomena analysis, for which a purely linguistic methodology is not
Zhao Yuanze +3 more
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On the Initialization of Long Short-Term Memory Networks [PDF]
, 2019 Weight initialization is important for faster convergence and stability of deep neural networks training. In this paper, a robust initialization method is developed to address the training instability in long short-term memory (LSTM) networks. It is based on a normalized random initialization of the network weights that aims at preserving the variance ...
Mehdipour Ghazi, Mostafa +6 more
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Continual Learning Long Short Term Memory [PDF]
Findings of the Association for Computational Linguistics: EMNLP 2020, 2020 Catastrophic forgetting in neural networks indicates the performance decreasing of deep learning models on previous tasks while learning new tasks. To address this problem, we propose a novel Continual Learning Long Short Term Memory (CL-LSTM) cell in Recurrent Neural Network (RNN) in this paper.
Qinghan Xue +6 more
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Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Paths [PDF]
Conference on Empirical Methods in Natural Language Processing, 2015 Relation classification is an important research arena in the field of natural language processing (NLP). In this paper, we present SDP-LSTM, a novel neural network to classify the relation of two entities in a sentence. Our neural architecture leverages
Yan Xu +5 more
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Applied Sciences, 2022 Ship position prediction plays a key role in the early warning and safety of inland waters and maritime navigation. Ship pilots must have in-depth knowledge of the future position of their ship and target ship in a specific time period when maneuvering ...
Long Qian +5 more
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