We study the implicit bias of optimization in robust empirical risk minimization (robust ERM) and its connection with robust generalization.

Generative Language Models (GLMs) have shown impressive performance in tasks such as text generation, understanding, and reasoning. However, the large model size poses challenges for practical deployment.

Modeling spatiotemporal brain dynamics from high-dimensional data, such as functional Magnetic Resonance Imaging (fMRI), is a formidable task in neuroscience.

The field of learning-augmented online algorithms has gained rapid prominence in recent years.