M. Piroozmand

UGD-LTR: an uncertainty-aware graph-based deep learning framework for learning to rank

The Uncertainty-aware graph-based deep learning to rank (UGD-LTR) framework tackles two critical gaps in learning to rank, and can train independently in distributed environments, and graph feature extraction can exploit distributed graph algorithms, providing a clear roadmap for future high-performance computing (HPC) deployment.