High-Dimensional Learning Dynamics

The High-dimensional Learning Dynamics (HiLD) workshop aims to advance our understanding of machine learning in the context of high-dimensional data, which is increasingly common as models and datasets grow in size. The workshop focuses on developing insights into how these machine learning algorithms behave in complex, high-dimensional settings, such as deep neural networks and large language models. By bringing together researchers from diverse fields, this workshop aims to develop both practical and theoretical strategies for more efficient and effective training of large-scale machine learning models. This research is critical as it can lead to better-informed decisions in model design and training, ultimately improving computational efficiency and outcomes in AI.