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Found 5 papers, 3 papers with code
PARSRec: Explainable Personalized Attention-fused Recurrent Sequential Recommendation Using Session Partial Actions
The emerging meta- and multi-verse landscape is yet another step towards the more prevalent use of already ubiquitous online markets.
A Data-Centric Approach for Training Deep Neural Networks with Less Data
While the availability of large datasets is perceived to be a key requirement for training deep neural networks, it is possible to train such models with relatively little data.
Distill-Net: Application-Specific Distillation of Deep Convolutional Neural Networks for Resource-Constrained IoT Platforms
Many Internet-of-Things (IoT) applications demand fast and accurate understanding of a few key events in their surrounding environment.
Fast and Energy-Efficient CNN Inference on IoT Devices
Convolutional Neural Networks (CNNs) exhibit remarkable performance in various machine learning tasks.
Hardware-oriented Approximation of Convolutional Neural Networks
One of the most important steps in accelerator development is hardware-oriented model approximation.
