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Denoising Pre-Training and Customized Prompt Learning for Efficient Multi-Behavior Sequential Recommendation
Its objective is to extract knowledge from extensive pre-training data and fine-tune the model for downstream tasks.
END4Rec: Efficient Noise-Decoupling for Multi-Behavior Sequential Recommendation
In recommendation systems, users frequently engage in multiple types of behaviors, such as clicking, adding to a cart, and purchasing.
OptScaler: A Hybrid Proactive-Reactive Framework for Robust Autoscaling in the Cloud
The reactive module provides a self-tuning estimator of CPU utilization to the optimization model.
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