Results 71 to 80 of about 1,741,359 (199)
Deep Learning with Long Short-Term Memory for Time Series Prediction
, 2018 Time series prediction can be generalized as a process that extracts useful information from historical records and then determines future values. Learning long-range dependencies that are embedded in time series is often an obstacle for most algorithms,
Chen, Xianfu +5 more
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Anais da Academia Brasileira de Ciências, 2000 Since William James (1890) first distinguished primary from secondary memory, equivalent to short- and long-term memory, respectively, it has been assumed that short-term memory processes are in charge of cognition while long-term memory is being ...
MÔNICA R.M. VIANNA +5 more
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Measuring Workload Differences Between Short-term Memory and Long-term Memory Scenarios in a Simulated Flight Environment [PDF]
, 1984 Four highly experienced Air Force pilots each flew four simulated flight scenarios. Two scenarios required a great deal of aircraft maneuvering. The other two scenarios involved less maneuvering, but required remembering a number of items.
Berg, S. L., Sheridan, T. B.
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Learning to Detect Violent Videos using Convolutional Long Short-Term Memory
, 2017 Developing a technique for the automatic analysis of surveillance videos in order to identify the presence of violence is of broad interest. In this work, we propose a deep neural network for the purpose of recognizing violent videos.
Lanz, Oswald, Sudhakaran, Swathikiran
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ILSTMA: Enhancing Accuracy and Speed of Long-Term and Short-Term Memory Architecture
InformationIn recent years, the rapid development of large language models (LLMs) has led to a growing consensus in the industry regarding the integration of long-term and short-term memory.
Zongyu Ming, Zimu Wu, Genlang Chen
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Evolving Long Short-Term Memory Networks [PDF]
, 2020 Machine learning techniques have been massively employed in the last years over a wide variety of applications, especially those based on deep learning, which obtained state-of-the-art results in several research fields. Despite the success, such techniques still suffer from some shortcomings, such as the sensitivity to their hyperparameters, whose ...
Vicente Coelho Lobo Neto +2 more
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Federated quantum long short-term memory (FedQLSTM)
Quantum Machine IntelligenceAbstractQuantum federated learning (QFL) can facilitate collaborative learning across multiple clients using quantum machine learning (QML) models, while preserving data privacy. Although recent advances in QFL span different tasks like classification while leveraging several data types, no prior work has focused on developing a QFL framework that ...
Chehimi, Mahdi +3 more
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Does New Zealand visitors follow the Joseph Effect? Some empirical evidence [PDF]
, 2011 The report departs from conventional time series analysis and investigates the existence of long memory (LRD) in the stream of daily visitors, arriving from various sources to New Zealand from 1997 to 2010, using selected estimators of the Hurst-exponent.
Foo, Dani
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Response Characterization for Auditing Cell Dynamics in Long Short-term Memory Networks
, 2018 In this paper, we introduce a novel method to interpret recurrent neural networks (RNNs), particularly long short-term memory networks (LSTMs) at the cellular level.
Amini, Alexander +5 more
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Long-Term Traffic Prediction Using Deep Learning Long Short-Term Memory
Smart CitiesTraffic conditions are a key factor in our society, contributing to quality of life and the economy, as well as access to professional, educational, and health resources. This emphasizes the need for a reliable road network to facilitate traffic fluidity
Ange-Lionel Toba +3 more
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