报告题目：Toward Edge General Intelligence with Agentic AI and Agentification报 告 人：Dusit Niyato, 新加坡南洋理工大学（NTU）计算与数据科学学院 President's Chair Professor报告时间：2025年9月26日 (星期五) 上午10:00  报告地点：信息科学与工程学院/网络空间安全学院 624报告厅邀 请 人：靳文强教授报告摘要:The rapid expansion of sixth-generation (6G) wireless networks and the Internet of Things (IoT) h...

 报告摘要：启发式方法被广泛用于处理复杂的搜索和优化问题。然而，启发式设计的手工设计往往非常繁琐，需要丰富的工作经验和知识。在本次演讲中，将介绍启发式进化（EoH），这是一种利用大语言模型（LLMs）和自动启发式设计（AHD）进化搜索的进化范式。EoH用自然语言表示启发学的思想，称为思想。之后它们被LLMs翻译成可执行代码。进化搜索框架中思想和代码的进化使其在生成高性能启发式方法方面非常有效和高效。三个广泛研究...

报告摘要: Generative models, which map a latent parameter space to instances in an ambient space, enjoy various applications in 3D Vision and related domains. A standard scheme of these models is probabilistic, which aligns the induced ambient distribution of a generative model from a prior distribution of the latent space with the empirical ambient distribution of training instances. While thi...

报告摘要: In recent years, the 3D vision community has witnessed a significant shift towards Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) as primary focal points. These innovations have fundamentally transformed how we represent 3D space and learn these representations through deep learning techniques with 2D image supervision. Existing research in NeRF and 3DGS can be broadly...