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 ...

A multi-task learning framework, DEMENTIA, has been developed by Prof. Li Hai and his team at the Hefei Institutes of ...

In order to solve the problem in the present, we developed a model named cross modal adaptive few-shot learning based on task dependence (COOPERATE for short). A feature extraction and task ...

Abstract: This article addressed the challenge of the task space trajectory planning problem for free-floating space robots ... These baseline trajectories serve as references for the post-processing.

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

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

To counter the sophisticated threats posed by advanced backdoor frameworks like UNIDOOR, the study underscores the importance ...

Reference examples of our in the box tasks are here Starting from version v2.141.0, the agent can now run on three OS architectures: x86, x64, and 32-bit ARM. When authoring a new task, you can check ...

What do you think were the best albums, songs and artists of the year? By The Learning Network Choose three to five works of art or culture to group in some way, then tell us why we should ...