Artificial Intelligence
Source:
https://bit.ly/2OGsNcI
An increasing number of information systems leverage AI techniques to provide effective services dealing with the complexity, the scale and the dynamic nature of data. Moreover, data is often naturally decentralized and users’ data privacy is at stake when cyber-attacks and data breaches occur.
This research focuses on the deployment of AI solutions in real-world scenarios, where
- latency constraints must be fulfilled in order to provide users with effective and efficient solutions;
- data and processing must be kept local to user’s devices, leveraging federated learning solutions on mobile-edge-cloud platforms.
Nicola Tonellotto
Assistant Professor of Computer Engineering
Nicola Tonellotto is Assistant Professor of Computer Engineering at the Information Engineering Department of the University of Pisa, Italy. His research interests include cloud computing, distributed systems, and Web information retrieval.
Publications
Efficient Document Re-Ranking for Transformers by Precomputing Term Representations
Deep pretrained transformer networks are effective at various ranking tasks, such as question answering and ad-hoc document ranking. …
Expansion via Prediction of Importance with Contextualization
The identification of relevance with little textual context is a primary challenge in passage retrieval. We address this problem with a …
Training Curricula for Open Domain Answer Re-Ranking
In precision-oriented tasks like answer ranking, it is more important to rank many relevant answers highly than to retrieve all …
A method to rank documents by a computer, using additive ensembles of regression trees and cache optimisation, and search engines using such a method
International Application Number PCT29914, filed by Tiscali S.p.A. on 17 June 2015.