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Stock Volatility Prediction Based on Transformer Model Using Mixed-Frequency Data
With the increasing volume of high-frequency data in the information age, both challenges and opportunities arise in the prediction of stock volatility.
An Empirical Study of Attention Networks for Semantic Segmentation
What's more, various methods utilize attention in semantic segmentation, but the conclusion of these methods is lacking.
EdgeMA: Model Adaptation System for Real-Time Video Analytics on Edge Devices
In this paper, we introduce EdgeMA, a practical and efficient video analytics system designed to adapt models to shifts in real-world video streams over time, addressing the data drift problem.
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