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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 …
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EdgeMA: Model Adaptation System for Real-Time Video Analytics on Edge Devices
Real-time video analytics on edge devices for changing scenes remains a difficult task. As edge devices are usually …
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EdgeMA: Model Adaptation System for Real-Time Video Analytics on Edge Devices
Machine Unlearning Methodology base on Stochastic Teacher Network
The rise of the phenomenon of the “right to be forgotten” has prompted research on machine unlearning, which grants data …
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Machine Unlearning Methodology base on Stochastic Teacher Network
Improving EEG-based Emotion Recognition by Fusing Time-frequency And Spatial Representations
Using deep learning methods to classify EEG signals can accurately identify people’s emotions. However, existing studies have …
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Improving EEG-based Emotion Recognition by Fusing Time-frequency And Spatial Representations
Improving Imbalanced Text Classification with Dynamic Curriculum Learning
Recent advances in pre-trained language models have improved the performance for text classification tasks. However, little attention …
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Improving Imbalanced Text Classification with Dynamic Curriculum Learning
Adaptive Few-Shot Learning Algorithm for Rare Sound Event Detection
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Augmentation-induced Consistency Regularization for Classification
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Blur the Linguistic Boundary: Interpreting Chinese Buddhist Sutra in English via Neural Machine Translation
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Debias the Black-Box: A Fair Ranking Framework via Knowledge Distillation
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Efficient Private Set Intersection Based on Functional Encryption
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