Superior resilience to poisoning and amenability to unlearning in quantum machine learning
Fuente:
arXiv
Guardado en:
| Autores principales: | Chen, Yu-Qin, Zhang, Shi-Xin |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Intrinsic preservation of plasticity in continual quantum learning
por: Chen, Yu-Qin, et al.
Publicado: (2025)
por: Chen, Yu-Qin, et al.
Publicado: (2025)
Quantum approximate optimization via learning-based adaptive optimization
por: Cheng, Lixue, et al.
Publicado: (2023)
por: Cheng, Lixue, et al.
Publicado: (2023)
Universal replication of chaotic characteristics by classical and quantum machine learning
por: Bai, Sheng-Chen, et al.
Publicado: (2024)
por: Bai, Sheng-Chen, et al.
Publicado: (2024)
Reinforcement learning-based architecture search for quantum machine learning
por: Rapp, Frederic, et al.
Publicado: (2024)
por: Rapp, Frederic, et al.
Publicado: (2024)
Fourier series weight in quantum machine learning
por: Atchade-Adelomou, Parfait, et al.
Publicado: (2023)
por: Atchade-Adelomou, Parfait, et al.
Publicado: (2023)
Opportunities and limitations of explaining quantum machine learning
por: Gil-Fuster, Elies, et al.
Publicado: (2024)
por: Gil-Fuster, Elies, et al.
Publicado: (2024)
Can machine learning for quantum-gas experiments be explainable?
por: Zwolak, I. B. Spielman amd J. P.
Publicado: (2026)
por: Zwolak, I. B. Spielman amd J. P.
Publicado: (2026)
Shadows of quantum machine learning
por: Jerbi, Sofiene, et al.
Publicado: (2023)
por: Jerbi, Sofiene, et al.
Publicado: (2023)
Understanding quantum machine learning also requires rethinking generalization
por: Gil-Fuster, Elies, et al.
Publicado: (2023)
por: Gil-Fuster, Elies, et al.
Publicado: (2023)
Variational decision diagrams for quantum-inspired machine learning applications
por: Vargas-Calderón, Vladimir, et al.
Publicado: (2025)
por: Vargas-Calderón, Vladimir, et al.
Publicado: (2025)
Prospects for quantum advantage in machine learning from the representability of functions
por: Masot-Llima, Sergi, et al.
Publicado: (2025)
por: Masot-Llima, Sergi, et al.
Publicado: (2025)
Structured quantum learning via em algorithm for Boltzmann machines
por: Kimura, Takeshi, et al.
Publicado: (2025)
por: Kimura, Takeshi, et al.
Publicado: (2025)
Symmetry breaking in geometric quantum machine learning in the presence of noise
por: Tüysüz, Cenk, et al.
Publicado: (2024)
por: Tüysüz, Cenk, et al.
Publicado: (2024)
A general learning scheme for classical and quantum Ising machines
por: Schmid, Ludwig, et al.
Publicado: (2023)
por: Schmid, Ludwig, et al.
Publicado: (2023)
Spectral methods: crucial for machine learning, natural for quantum computers?
por: Belis, Vasilis, et al.
Publicado: (2026)
por: Belis, Vasilis, et al.
Publicado: (2026)
Benchmarking quantum machine learning kernel training for classification tasks
por: Alvarez-Estevez, Diego
Publicado: (2024)
por: Alvarez-Estevez, Diego
Publicado: (2024)
Dynamical simulation via quantum machine learning with provable generalization
por: Gibbs, Joe, et al.
Publicado: (2022)
por: Gibbs, Joe, et al.
Publicado: (2022)
Information plane and compression-gnostic feedback in quantum machine learning
por: Haboury, Nathan, et al.
Publicado: (2024)
por: Haboury, Nathan, et al.
Publicado: (2024)
Generative quantum machine learning via denoising diffusion probabilistic models
por: Zhang, Bingzhi, et al.
Publicado: (2023)
por: Zhang, Bingzhi, et al.
Publicado: (2023)
Blind quantum machine learning with quantum bipartite correlator
por: Li, Changhao, et al.
Publicado: (2023)
por: Li, Changhao, et al.
Publicado: (2023)
Dimension reduction with structure-aware quantum circuits for hybrid machine learning
por: Daskin, Ammar
Publicado: (2025)
por: Daskin, Ammar
Publicado: (2025)
Potential and limitations of random Fourier features for dequantizing quantum machine learning
por: Sweke, Ryan, et al.
Publicado: (2023)
por: Sweke, Ryan, et al.
Publicado: (2023)
The role of data-induced randomness in quantum machine learning classification tasks
por: Casas, Berta, et al.
Publicado: (2024)
por: Casas, Berta, et al.
Publicado: (2024)
A semi-agnostic ansatz with variable structure for quantum machine learning
por: Bilkis, M., et al.
Publicado: (2021)
por: Bilkis, M., et al.
Publicado: (2021)
Scalable quantum dynamics compilation via quantum machine learning
por: Zhang, Yuxuan, et al.
Publicado: (2024)
por: Zhang, Yuxuan, et al.
Publicado: (2024)
The interplay of robustness and generalization in quantum machine learning
por: Berberich, Julian, et al.
Publicado: (2025)
por: Berberich, Julian, et al.
Publicado: (2025)
Training-efficient density quantum machine learning
por: Coyle, Brian, et al.
Publicado: (2024)
por: Coyle, Brian, et al.
Publicado: (2024)
On fundamental aspects of quantum extreme learning machines
por: Xiong, Weijie, et al.
Publicado: (2023)
por: Xiong, Weijie, et al.
Publicado: (2023)
Towards provably efficient quantum algorithms for large-scale machine-learning models
por: Liu, Junyu, et al.
Publicado: (2023)
por: Liu, Junyu, et al.
Publicado: (2023)
Better than classical? The subtle art of benchmarking quantum machine learning models
por: Bowles, Joseph, et al.
Publicado: (2024)
por: Bowles, Joseph, et al.
Publicado: (2024)
Robust estimation of the intrinsic dimension of data sets with quantum cognition machine learning
por: Candelori, Luca, et al.
Publicado: (2024)
por: Candelori, Luca, et al.
Publicado: (2024)
Application of quantum machine learning using quantum kernel algorithms on multiclass neuron M type classification
por: Vasques, Xavier, et al.
Publicado: (2025)
por: Vasques, Xavier, et al.
Publicado: (2025)
Symmetry-invariant quantum machine learning force fields
por: Le, Isabel Nha Minh, et al.
Publicado: (2023)
por: Le, Isabel Nha Minh, et al.
Publicado: (2023)
Bridging quantum and classical computing for partial differential equations through multifidelity machine learning
por: Jacob, Bruno, et al.
Publicado: (2025)
por: Jacob, Bruno, et al.
Publicado: (2025)
Bayesian quantum sensing using graybox machine learning
por: Youssry, Akram, et al.
Publicado: (2026)
por: Youssry, Akram, et al.
Publicado: (2026)
Photovoltaic power forecasting using quantum machine learning
por: Sagingalieva, Asel, et al.
Publicado: (2023)
por: Sagingalieva, Asel, et al.
Publicado: (2023)
Universal scaling laws in quantum-probabilistic machine learning by tensor network towards interpreting representation and generalization powers
por: Bai, Sheng-Chen, et al.
Publicado: (2024)
por: Bai, Sheng-Chen, et al.
Publicado: (2024)
Fundamentals of quantum Boltzmann machine learning with visible and hidden units
por: Wilde, Mark M.
Publicado: (2025)
por: Wilde, Mark M.
Publicado: (2025)
TQml Simulator: optimized simulation of quantum machine learning
por: Kuzmin, Viacheslav, et al.
Publicado: (2025)
por: Kuzmin, Viacheslav, et al.
Publicado: (2025)
The complexity of quantum support vector machines
por: Gentinetta, Gian, et al.
Publicado: (2022)
por: Gentinetta, Gian, et al.
Publicado: (2022)
Ejemplares similares
-
Intrinsic preservation of plasticity in continual quantum learning
por: Chen, Yu-Qin, et al.
Publicado: (2025) -
Quantum approximate optimization via learning-based adaptive optimization
por: Cheng, Lixue, et al.
Publicado: (2023) -
Universal replication of chaotic characteristics by classical and quantum machine learning
por: Bai, Sheng-Chen, et al.
Publicado: (2024) -
Reinforcement learning-based architecture search for quantum machine learning
por: Rapp, Frederic, et al.
Publicado: (2024) -
Fourier series weight in quantum machine learning
por: Atchade-Adelomou, Parfait, et al.
Publicado: (2023)