Quantum Algorithms for Tensor-SVD
| dc.contributor.author | JOJO, JEZER | en_US |
| dc.contributor.author | Khandelwal, Ankit | en_US |
| dc.contributor.author | Chandra, M. Girish | en_US |
| dc.contributor.department | Dept. of Physics | en_US |
| dc.date.accessioned | 2025-04-19T05:42:09Z | |
| dc.date.available | 2025-04-19T05:42:09Z | |
| dc.date.issued | 2024-09 | en_US |
| dc.description.abstract | A promising area of applications for quantum computing is in linear algebra problems. In this work, we introduce two new quantum t-SVD (tensor-SVD) algorithms. The first algorithm is largely based on previous work that proposed a quantum t-SVD algorithm for context-aware recommendation systems. The new algorithm however seeks to address and fix certain drawbacks in the original, and is fundamentally different in its approach compared to the existing work. The second algorithm proposed uses a hybrid variational approach largely based on a known variational quantum SVD algorithm. | en_US |
| dc.identifier.citation | 2024 IEEE International Conference on Quantum Computing and Engineering (QCE) | en_US |
| dc.identifier.doi | https://doi.org/10.1109/QCE60285.2024.00018 | en_US |
| dc.identifier.isbn | 979-8-3315-4137-8 | |
| dc.identifier.isbn | 979-8-3315-4138-5 | |
| dc.identifier.sourcetitle | 2024 IEEE International Conference on Quantum Computing and Engineering (QCE) | en_US |
| dc.identifier.uri | https://doi.org/10.1109/QCE60285.2024.00018 | |
| dc.identifier.uri | http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/9650 | |
| dc.language.iso | en | en_US |
| dc.publication.originofpublisher | Foreign | en_US |
| dc.publisher | IEEE | en_US |
| dc.subject | Machine learning algorithms | en_US |
| dc.subject | Quantum algorithm | en_US |
| dc.subject | Linear algebra | en_US |
| dc.subject | Recommender systems | en_US |
| dc.subject | 2024 | en_US |
| dc.title | Quantum Algorithms for Tensor-SVD | en_US |
| dc.type | Conference Papers | en_US |