mlsanityData to 7 Oct 2026

Quantum Circuit C^*-algebra Net

arXiv 2404.06218 ↗First posted 9 Apr 2024cs.LG math.OA quant-phcited by 0

Not on the map. Why?

Abstract (arXiv)

This paper introduces quantum circuit C^*-algebra net, which provides a connection between C^*-algebra nets proposed in classical machine learning and quantum circuits. Using C^*-algebra, a generalization of the space of complex numbers, we can represent quantum gates as weight parameters of a neural network. By introducing additional parameters, we can induce interaction among multiple circuits constructed by quantum gates. This interaction enables the circuits to share information among them, which contributes to improved generalization performance in machine learning tasks. As an application, we propose to use the quantum circuit C^*-algebra net to encode classical data into quantum states, which enables us to integrate classical data into quantum algorithms. Numerical results demonstrate that the interaction among circuits improves performance significantly in image classification, and encoded data by the quantum circuit C^*-algebra net are useful for downstream quantum machine learning tasks.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 17 of its 31 references that are in the map. First posted on arXiv 9 Apr 2024.

Builds on

17 of 31 references.

References · 17

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  3. 2017Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithmscited by 4,283
  4. 2018Supervised learning with quantum enhanced feature spacescited by 654
  5. 2018Deep Learning for Classical Japanese Literaturecited by 415
  6. 2021Ensemble deep learning: A reviewcited by 283
  7. 2016Full-Capacity Unitary Recurrent Neural Networkscited by 90
  8. 2020Efficient Riemannian Optimization on the Stiefel Manifold via the Cayley Transformcited by 79
  9. 2016Decentralized Collaborative Learning of Personalized Models over Networkscited by 73
  10. 2017Personalized and Private Peer-to-Peer Machine Learningcited by 54
  11. 2021Reproducing kernel Hilbert C*-module and kernel mean embeddingscited by 10
  12. 2022C^*-algebra Net: A New Approach Generalizing Neural Network Parameters to C^*-algebracited by 9
5 more
  1. 2022Learning in RKHM: a C^*-Algebraic Twist for Kernel Machinescited by 7
  2. 2023Deep Learning with Kernels through RKHM and the Perron-Frobenius Operatorcited by 7
  3. 2023Noncommutative C^*-algebra Net: Learning Neural Networks with Powerful Product Structure in C^*-algebracited by 4
  4. 2023MNISQ: A Large-Scale Quantum Circuit Dataset for Machine Learning on/for Quantum Computers in the NISQ eracited by 3
  5. 2024C^*-Algebraic Machine Learning: Moving in a New Directioncited by 1

Built on by

Not cited yet.