Distilling Datasets into Shallow Circuits for Quantum Machine Learning
quant-ph
Submitted: 2026-09-23
Updated: 2026-09-23
Terminology
Sources
- Super-Samples from Kernel Herding
- Quantum computing with Qiskit
- Adam: A Method for Stochastic Optimization
- Structured Unitary Tensor Network Representations for Circuit-Efficient Quantum Data Encoding
- Transformation of quantum states using uniformly controlled rotations
- Active Learning for Convolutional Neural Networks: A Core-Set Approach
- An Empirical Study of Example Forgetting during Deep Neural Network Learning
- Dataset Distillation
Related papers
- Reconquering Bell sampling on qudits: stabilizer learning and testing, quantum pseudorandomness bounds, and more
- Encrypted clones can leak: Classification of informative subsets in Quantum Encrypted Cloning
- Polynomial-time classical and quantum simulation of quantum impurity models
- Theory of quantum-enhanced interferometry with general Markovian light sources
- A convergent hierarchy of spectral gap certificates for qubit Hamiltonians
- Universal Bound and Phase Transition in Many-Body Fermionic Non-Gaussianity