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ILSTMA: Enhancing Accuracy and Speed of Long-Term and Short-Term Memory Architecture

Information
In 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
doaj   +1 more source

Federated quantum long short-term memory (FedQLSTM)

Quantum Machine Intelligence
AbstractQuantum 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, Chen, Samuel Yen-Chi, Saad, Walid, Yoo, Shinjae   +3 more
openaire   +4 more sources

Short-term memory and long-term memory are still different.

Psychological Bulletin, 2017
A commonly expressed view is that short-term memory (STM) is nothing more than activated long-term memory. If true, this would overturn a central tenet of cognitive psychology-the idea that there are functionally and neurobiologically distinct short- and long-term stores.
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Quantum Long Short-Term Memory for Drug Discovery

EPJ Quantum Technology
Abstract Quantum computing combined with machine learning (ML) is an extremely promising research area, with numerous studies demonstrating that quantum machine learning (QML) is expected to solve scientific problems more effectively than classical ML.
Liang Zhang, Yin Xu, Mohan Wu, Liang Wang, Hua Xu   +4 more
openaire   +2 more sources

Long-Term Traffic Prediction Using Deep Learning Long Short-Term Memory

Smart Cities
Traffic 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, Sameer Kulkarni, Wael Khallouli, Timothy Pennington   +3 more
doaj   +1 more source

The long memory of newspapers' subscriptions: between the short-run and persistence response [PDF]

The mainstream of marketing time series analysis has shifted from classical short-range dependence (ARMA, transfer functions and VAR models). However, in cases where purchase decisions entail some commitment (e.g., a subscription selling periodic use of ...
Mercedes Esteban Bravo, Jose M. Vidal-Sanz   +1 more
core  

Long Short-Term Memory with Dynamic Skip Connections

Proceedings of the AAAI Conference on Artificial Intelligence, 2019
In recent years, long short-term memory (LSTM) has been successfully used to model sequential data of variable length. However, LSTM can still experience difficulty in capturing long-term dependencies. In this work, we tried to alleviate this problem by introducing a dynamic skip connection, which can learn to directly connect two dependent words ...
Tao Gui, Qi Zhang 0001, Lujun Zhao, Yaosong Lin, Minlong Peng, Jingjing Gong, Xuanjing Huang 0001   +6 more
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Love is . . . an abstract word: the influence of phonological and semantic factors on verbal short-term memory in Williams syndrome [PDF]

, 2005
It has been claimed that verbal short-term memory in Williams syndrome is characterised by an over-use of phonological coding alongside a reduced contribution of lexical semantics.
Thomas, Michael S.C., Karmiloff-Smith, Annette, Laing, E., Grant, J., Parmigiani, C., Ewing, S.   +5 more
core   +1 more source

Short- and long-term memory: differential involvement of neurotransmitter systems and signal transduction cascades

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, LUCIANA A. IZQUIERDO, DANIELA M. BARROS, ROGER WALZ, JORGE H. MEDINA, IVÁN IZQUIERDO   +5 more
doaj   +1 more source

Long short-term memory networks in memristor crossbars

CoRR, 2018
Recent breakthroughs in recurrent deep neural networks with long short-term memory (LSTM) units has led to major advances in artificial intelligence. State-of-the-art LSTM models with significantly increased complexity and a large number of parameters, however, have a bottleneck in computing power resulting from limited memory capacity and data ...
Can Li 0024, Zhongrui Wang, Mingyi Rao, Daniel Belkin, Wenhao Song, Hao Jiang 0017, Peng Yan, Yunning Li, Peng Lin, Miao Hu 0002, Ning Ge 0001, John Paul Strachan, Mark Barnell, Qing Wu 0002, R. Stanley Williams, J. Joshua Yang, Qiangfei Xia   +16 more
openaire   +3 more sources