Sebastian Bruch

TF-Ranking

2019

Learning-to-Rank deals with maximizing the utility of a list of examples presented to the user, with items of higher relevance being prioritized. It has several practical applications such as large-scale search, recommender systems, document summarization …

Learning Representations for Axis-Aligned Decision Forests through Input Perturbation

2020 · arXiv (Cornell University)

Axis-aligned decision forests have long been the leading class of machine learning algorithms for modeling tabular data. In many applications of machine learning such as learning-to-rank, decision forests deliver remarkable performance. They also possess other …