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PEPT: Expert Finding Meets Personalized Pre-training
For alleviating this, we present a personalized pre-training and fine-tuning paradigm, which could effectively learn expert interest and expertise simultaneously.
CNN-based Local Vision Transformer for COVID-19 Diagnosis
Deep learning technology can be used as an assistive technology to help doctors quickly and accurately identify COVID-19 infections.
Multi-scale alignment and Spatial ROI Module for COVID-19 Diagnosis
However, in CT and CXR images, the infected area occupies only a small part of the image.
Data Agnostic Filter Gating for Efficient Deep Networks
To deploy a well-trained CNN model on low-end computation edge devices, it is usually supposed to compress or prune the model under certain computation budget (e. g., FLOPs).
Neural Review Rating Prediction with Hierarchical Attentions and Latent Factors
In this paper, we propose a hierarchical attention model fusing latent factor model for rating prediction with reviews, which can focus on important words and informative reviews.
