mlsanityData to 7 Oct 2026

Quantum Optimization for Training Quantum Neural Networks

arXiv 2103.17047 ↗First posted 31 Mar 2021quant-ph cs.AI cs.LGcited by 6

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Abstract (arXiv)

Training quantum neural networks (QNNs) using gradient-based or gradient-free classical optimisation approaches is severely impacted by the presence of barren plateaus in the cost landscapes. In this paper, we devise a framework for leveraging quantum optimisation algorithms to find optimal parameters of QNNs for certain tasks. To achieve this, we coherently encode the cost function of QNNs onto relative phases of a superposition state in the Hilbert space of the network parameters. The parameters are tuned with an iterative quantum optimisation structure using adaptively selected Hamiltonians. The quantum mechanism of this framework exploits hidden structure in the QNN optimisation problem and hence is expected to provide beyond-Grover speed up, mitigating the barren plateau issue.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 13 of its 77 references that are in the map. First posted on arXiv 31 Mar 2021.

Builds on

13 of 77 references.

References · 13

  1. 2018Barren plateaus in quantum neural network training landscapescited by 624
  2. 2020Noise-Induced Barren Plateaus in Variational Quantum Algorithmscited by 192
  3. 2020Entanglement Induced Barren Plateauscited by 101
  4. 2020Layerwise learning for quantum neural networkscited by 87
  5. 2020Experimental Quantum Generative Adversarial Networks for Image Generationcited by 83
  6. 2020Effect of barren plateaus on gradient-free optimizationcited by 79
  7. 2019Learning to learn with quantum neural networks via classical neural networkscited by 55
  8. 2019Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problemscited by 30
  9. 2018Learning and Inference on Generative Adversarial Quantum Circuitscited by 22
  10. 2020Policy Gradient based Quantum Approximate Optimization Algorithmcited by 14
  11. 2019Reinforcement-Learning-Based Variational Quantum Circuits Optimization for Combinatorial Problemscited by 6
  12. 2020Low depth mechanisms for quantum optimizationcited by 5
1 more
  1. 2017A Quantum Walk Enhanced Grover Search Algorithm for Global Optimizationcited by 1

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Cited by year

Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 3.

6 papers.

  1. 2021Equivalence of quantum barren plateaus to cost concentration and narrow gorgescited by 53
  2. 2023Variational Quantum Neural Networks (VQNNS) in Image Classificationcited by 4
  3. 2024Graph Neural Networks on Quantum Computerscited by 4
  4. 2022Quantum Extremal Learningcited by 3
  5. 2024Automatic re-calibration of quantum devices by reinforcement learningcited by 0
  6. 2024Hybrid Classical-Quantum architecture for vectorised image classification of hand-written sketchescited by 0