Research

Applied Quantum Computing

• Pellini, R., Ferrari Dacrema, M.
  Analyzing the effectiveness of quantum annealing with meta-learning.
  Quantum Machine Intelligence 6, 48 (2024).
  https://doi.org/10.1007/s42484-024-00179-8
• Carugno, C., Ferrari Dacrema, M., Cremonesi, P.
  Adaptive Learning for Quantum Linear Regression.
  International Conference on Quantum Computing and Engineering  (2024).
• Turati, G., Ferrari Dacrema, M., Cremonesi, P.
  Benchmarking Adaptative Variational Quantum Algorithms on QUBO Instances.
  International Conference on Quantum Computing and Engineering  (2023).
  https://doi.org/10.1109/QCE57702.2023.00053
• Mato, K.; Mengoni, R.; Ottaviani, D.; Palermo, G.;
  Quantum molecular unfolding.
  Quantum Science and Technology (2022), 7, 3.
  https://doi.org/10.1088/2058-9565/ac73af
• Carugno, C., Ferrari Dacrema, M., Cremonesi, P.
  Evaluating the job shop scheduling problem on a D-wave quantum annealer.
  Nature Scientific Reports 12, 6539 (2022).
  https://doi.org/10.1038/s41598-022-10169-0
• Ferrari Dacrema, M., Moroni F., Nembrini R., Ferro N., Faggioli G., Cremonesi, P.
  Towards Feature Selection for Ranking and Classification Exploiting Quantum Annealers,
  SIGIR ’22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval.
  https://doi.org/10.1145/3477495.3531755
• Nembrini, R.; Ferrari Dacrema, M.; Cremonesi, P.
  Feature Selection for Recommender Systems with Quantum Computing.
  Entropy (2021), 23, 970.
  https://doi.org/10.3390/e23080970
• Ferrari Dacrema, M.; Nembrini, R.; Zhou, T.; Cremonesi, P.
  Quantum Annealing Linear Regression For Collaborative Filtering Recommendations.
  European Quantum Technologies Conference, 2021.
• Ferrari Dacrema, M.; Felicioni, N.; Cremonesi, P.
  Personalizing Video Recommendation Layout with Quantum Annealing.
  European Quantum Technologies Conference, 2021.
• Ferrari Dacrema, M.; Felicioni, N.; Cremonesi, P.
  Optimizing the Selection of Recommendation Carousels with Quantum Computing.
  Fifteenth ACM Conference on Recommender Systems, 2021, 691–696.
  https://dl.acm.org/doi/abs/10.1145/3460231.3478853

Quantum Computing Algorithms

•  Simone Perriello, Alessandro Barenghi, Gerardo Pelosi:
  A Complete Quantum Circuit to Solve the Information Set Decoding Problem.
  IEEE International Conference on Quantum Computing and Engineering, QCE 2021
  https://doi.org/10.1109/QCE52317.2021.00056
• Simone Perriello, Alessandro Barenghi, Gerardo Pelosi:
  A Quantum Circuit to Speed-Up the Cryptanalysis of Code-Based Cryptosystems.
  Security and Privacy in Communication Networks – 17th EAI International Conference, SecureComm 2021 (ed. Springer)
  https://doi.org/10.1007/978-3-030-90022-9_25

Quantum Machine Learning

• Armando Bellante, Alessandro Luongo, Stefano Zanero:
  Quantum algorithms for SVD-based data representation and analysis.
  Quantum Machine Intelligence 4.2 (2022) (ed. Springer)
  https://doi.org/10.1007/s42484-022-00076-y
• Armando Bellante, Stefano Zanero:
  Quantum matching pursuit: A quantum algorithm for sparse representations.
  Poster session at QIP 2022.
  Physical Review A, 2022, 105.2: 022414
  https://doi.org/10.1103/PhysRevA.105.022414
• Armando Bellante:
  Quantum data representations for audio and natural language processing.
  Quantum natural language processing 2022 (org. by Cambridge Quantum Computing)
  Link to the talk
• Armando Bellante, Gopikrishnan Muraleedharan, Rolando Somma:
  Solving the quantum simulation problem via signal analysis.
  2021 Virtual Theoretical Division Lightning Talk Series (Los Alamos National Laboratory)
  https://doi.org/10.2172/1836977
• Alessandro Luongo, Armando Bellante:
  The quantumalgorithms.org project.
  IEEE, International Conference on Quantum Computing and Engineering, QCE 2021, Workshop:
  Developing Effective Methodologies to Teach Quantum Information Science to Early-Stage Learners