In this study, a novel approach to load time series situational prediction is proposed, which integrates spatial correlations of heterogeneous load resources through the application of Random Matrix ...

We use contrastive learning in both stages of training. Starting from the bare CLIP features as a baseline, experimental results show that the task-oriented fine-tuning and the carefully crafted ...

Meanwhile, this paper proposes a Federated Learning and Cloud-Edge Gaming with Incentive-Driven (FL-CEGID) algorithm for dynamic task offloading in IoV. Our proposed algorithm optimizes vehicle and ...

To this end, an approach based on Deep Reinforcement Learning (DRL) is presented in this paper, termed DVTP, which integrates Variational Graph Attention Networks (VGAT) and Transformer models to ...

How are students expected to gain work experience while in school? The answer is integrating paid work-based learning into their programs. Work-based learning is a teaching method that combines ...

Companies need technology that not only improves order fulfillment metrics, but helps retain workers by making it easier to ...

Reinforcement learning holds immense promise for robotic control, as it enables autonomous agents to learn through trial and ...

AI agents today struggle with efficiently mastering multiple tasks due to their heavy reliance on prompts. The traditional ...

After hours: February 7 at 7:27:33 PM EST Loading Chart for TASK ...

AI technology is everywhere, from phones to drive-through ordering systems. Given that companies like Google, Microsoft and ...

This is a simple TODO list application that allows users to add, view, update, and delete tasks. The application also provides a feature to analyze the status of tasks using a pie chart.