Abstract: Semi-supervised domain generalization (SSDG) has recently emerged as a potential research topic. Compared to domain generalization, SSDG represents a realistic and challenging goal, which ...

Abstract: Despite domain generalization (DG) has significantly addressed the performance degradation of pre-trained models caused by domain shifts, it often falls short in real-world deployment.

Agentic AI promises autonomy, but production systems expose its fragility. Dynatrace’s Perform keynote shows why ...

We propose a novel deep learning framework, STGCN, to tackle time series prediction problem in traffic domain. Instead of applying regular convolutional and recurrent units, we formulate the problem ...