Riccardo Nembrini

According to our database, Riccardo Nembrini authored at least 7 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Reinforcement Learning for Variational Quantum Circuits Design.

Simone Foderà, Gloria Turati, Riccardo Nembrini, Maurizio Ferrari Dacrema, Paolo Cremonesi

CoRR, 2024

An Application of Reinforcement Learning for Minor Embedding in Quantum Annealing (Short Paper).

Riccardo Nembrini, Maurizio Ferrari Dacrema, Paolo Cremonesi

Proceedings of the International Workshop on AI for Quantum and Quantum for AI (AIQxQIA 2024) co-located with 23rd International Conference of the Italian Association for Artificial Intelligence (AIxIA 2024), November 25, 2024

Reinforcement Learning for Variational Quantum Circuit Design.

Simone Foderà, Gloria Turati, Riccardo Nembrini, Maurizio Ferrari Dacrema, Paolo Cremonesi

Proceedings of the International Workshop on AI for Quantum and Quantum for AI (AIQxQIA 2024) co-located with 23rd International Conference of the Italian Association for Artificial Intelligence (AIxIA 2024), November 25, 2024

2022

Towards Feature Selection for Ranking and Classification Exploiting Quantum Annealers.

Maurizio Ferrari Dacrema, Fabio Moroni, Riccardo Nembrini, Nicola Ferro, Guglielmo Faggioli, Paolo Cremonesi

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Towards Recommender Systems with Community Detection and Quantum Computing.

Riccardo Nembrini, Costantino Carugno, Maurizio Ferrari Dacrema, Paolo Cremonesi

Proceedings of the RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18, 2022

Feature Selection via Quantum Annealers for Ranking and Classification Tasks.

Maurizio Ferrari Dacrema, Fabio Moroni, Riccardo Nembrini, Nicola Ferro, Guglielmo Faggioli, Paolo Cremonesi

Proceedings of the 12th Italian Information Retrieval Workshop 2022, 2022

2021

Feature Selection for Recommender Systems with Quantum Computing.

Riccardo Nembrini, Maurizio Ferrari Dacrema, Paolo Cremonesi

Entropy, 2021