mlsanityData to 7 Oct 2026

Projection Valued Measure-based Quantum Machine Learning for Multi-Class Classification

arXiv 2210.16731 ↗First posted 30 Oct 2022quant-ph cs.AI cs.LGcited by 4

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Abstract (arXiv)

In recent years, quantum machine learning (QML) has been actively used for various tasks, e.g., classification, reinforcement learning, and adversarial learning. However, these QML studies are unable to carry out complex tasks due to scalability issues on input and output which is currently the biggest hurdle in QML. Therefore, the purpose of this paper is to overcome the problem of scalability. Motivated by this challenge, we focus on projection-valued measurements (PVM) which utilize the nature of probability amplitude in quantum statistical mechanics. By leveraging PVM, the output dimension is expanded from q, which is the number of qubits, to 2q. We propose a novel QML framework that utilizes PVM for multi-class classification. Our framework is proven to outperform the state-of-the-art (SOTA) methodologies with various datasets, assuming no more than 6 qubits are used. Furthermore, our PVM-based QML shows about 42.2% better performance than the SOTA framework.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 16 of its 34 references that are in the map. First posted on arXiv 30 Oct 2022.

Builds on

16 of 34 references.

References · 16

  1. 2017ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Modelscited by 656
  2. 2020Absence of Barren Plateaus in Quantum Convolutional Neural Networkscited by 124
  3. 2021QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuitscited by 97
  4. 2021Federated Quantum Machine Learningcited by 82
  5. 2018Continuous-variable quantum neural networkscited by 74
  6. 2020Communication-Efficient and Distributed Learning Over Wireless Networks: Principles and Applicationscited by 62
  7. 2021Quantum Federated Learning with Quantum Datacited by 53
  8. 2022Quantum Multi-Agent Reinforcement Learning via Variational Quantum Circuit Designcited by 25
  9. 2022Slimmable Quantum Federated Learningcited by 23
  10. 2022Quantum Multi-Agent Meta Reinforcement Learningcited by 23
  11. 2021Quantum Neural Networks: Concepts, Applications, and Challengescited by 21
  12. 2022Classical-to-quantum convolutional neural network transfer learningcited by 18
4 more
  1. 2022Scalable Quantum Convolutional Neural Networkscited by 5
  2. 2022Dual-Frequency Quantum Phase Estimation Mitigates the Spectral Leakage of Quantum Algorithmscited by 4
  3. 20223D Scalable Quantum Convolutional Neural Networks for Point Cloud Data Processing in Classification Applicationscited by 4
  4. 2022Training Hybrid Classical-Quantum Classifiers via Stochastic Variational Optimizationcited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 2; 2024: 0; 2025: 0; 2026: 1.

4 papers.

  1. 2023Quantum Multi-Agent Reinforcement Learning for Autonomous Mobility Cooperationcited by 6
  2. 2022Quantum Split Neural Network Learning using Cross-Channel Poolingcited by 4
  3. 2023MORE: Measurement and Correlation Based Variational Quantum Circuit for Multi-classificationcited by 2
  4. 2026Empirical Study of Observable Sets in Multiclass Quantum Classificationcited by 0