Rossano Venturini

Distilled Neural Networks for Efficient Learning to Rank

2022 · IEEE Transactions on Knowledge and Data Engineering

Recent studies in Learning to Rank have shown the possibility to effectively distill a neural network from an ensemble of regression trees. This result leads neural networks to become a natural competitor of tree-based ensembles …

Faster Wavelet Tree Queries

2023 · arXiv (Cornell University)

Given a text, rank and select queries return the number of occurrences of a character up to a position (rank) or the position of a character with a given rank (select). These queries have applications …

OnPair: Short Strings Compression for Fast Random Access

2025 · arXiv (Cornell University)

We present OnPair, a dictionary-based compression algorithm designed to meet the needs of in-memory database systems that require both high compression and fast random access. Existing methods either achieve strong compression ratios at significant computational …

QuickScorer

2015

Learning-to-Rank models based on additive ensembles of regression trees have proven to be very effective for ranking query results returned by Web search engines, a scenario where quality and efficiency requirements are very demanding. Unfortunately, …