Browsing by Subject "Task analysis"
Now showing items 1-5 of 5
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BERT2OME: Prediction of 2′-O-methylation modifications from RNA sequence by transformer architecture based on BERT
(IEEE, 2023-06)Recent work on language models has resulted in state-of-the-art performance on various language tasks. Among these, Bidirectional Encoder Representations from Transformers (BERT) has focused on contextualizing word embeddings ... -
Deep reinforcement based power allocation for the max-min optimization in non-orthogonal multiple access
(IEEE, 2020)NOMA is a radio access technique that multiplexes several users over the frequency resource and provides high throughput and fairness among different users. The maximization of the minimum the data-rate, also known as ... -
Deep transformer-based asset price and direction prediction
(IEEE, 2024)The field of algorithmic trading, driven by deep learning methodologies, has garnered substantial attention in recent times. Within this domain, transformers, convolutional neural networks, and patch embedding-based ... -
Influence of culture, transparency, trust, and degree of automation on automation use
(IEEE, 2020-06)The reported study compares groups of 120 participants each, from the United States (U.S.), Taiwan (TW), and Turkey (TK), interacting with versions of an automated path planner that vary in transparency and degree of ... -
Modeling the development of infant imitation using inverse reinforcement learning
(IEEE, 2018-09)Little is known about the computational mechanisms of how imitation skills develop along with infant sensorimotor learning. In robotics, there are several well developed frameworks for imitation learning or so called ...
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