153 citations · 213 across the 17 of their papers we have counts for
22 papers
Early Exit Strategies for Approximate k-NN Search in Dense Retrieval
Francesco Busolin, Claudio Lucchese, Franco Maria Nardini +3
Learned dense representations are a popular family of techniques for encoding queries and documents using high-dimensional embeddings, which enable retrieval by performing approxim…
A Learning-to-Rank Formulation of Clustering-Based Approximate Nearest Neighbor Search
Thomas Vecchiato, Claudio Lucchese, Franco Maria Nardini +1
A critical piece of the modern information retrieval puzzle is approximate nearest neighbor search. Its objective is to return a set of data points that are closest to a query…
Verifiable Boosted Tree Ensembles
Stefano Calzavara, Lorenzo Cazzaro, Claudio Lucchese +1
Verifiable learning advocates for training machine learning models amenable to efficient security verification. Prior research demonstrated that specific classes of decision tree e…
Efficient and Effective Tree-based and Neural Learning to Rank
Sebastian Bruch, Claudio Lucchese, Franco Maria Nardini
This monograph takes a step towards promoting the study of efficiency in the era of neural information retrieval by offering a comprehensive survey of the literature on efficiency…
Fast Inference of Tree Ensembles on ARM Devices
Simon Koschel, Sebastian Buschjäger, Claudio Lucchese +1
With the ongoing integration of Machine Learning models into everyday life, e.g. in the form of the Internet of Things (IoT), the evaluation of learned models becomes more and more…
A Theoretical Framework for AI Models Explainability with Application in Biomedicine
Matteo Rizzo, Alberto Veneri, Andrea Albarelli +3
EXplainable Artificial Intelligence (XAI) is a vibrant research topic in the artificial intelligence community, with growing interest across methods and domains. Much has been writ…