Showing 281 - 300 results of 2,875 for search '(( algorithm from function ) OR ( algorithm ((within function) OR (python function)) ))', query time: 0.38s Refine Results
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    Flow chart diagram of blind quantum algorithm. by Sultan H. Almotiri (14029251)

    Published 2024
    “…Our study addresses five major components of the quantum method to overcome these challenges: lattice-based cryptography, fully homomorphic algorithms, quantum key distribution, quantum hash functions, and blind quantum algorithms. …”
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    Rosenbrock function losses for . by Shikun Chen (14625352)

    Published 2025
    “…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
  9. 289

    Rosenbrock function losses for . by Shikun Chen (14625352)

    Published 2025
    “…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
  10. 290

    Levy function losses for . by Shikun Chen (14625352)

    Published 2025
    “…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
  11. 291

    Rastrigin function losses for . by Shikun Chen (14625352)

    Published 2025
    “…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
  12. 292

    Levy function losses for . by Shikun Chen (14625352)

    Published 2025
    “…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
  13. 293

    Rastrigin function losses for . by Shikun Chen (14625352)

    Published 2025
    “…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
  14. 294

    Levy function losses for . by Shikun Chen (14625352)

    Published 2025
    “…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
  15. 295

    Levy function losses for . by Shikun Chen (14625352)

    Published 2025
    “…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
  16. 296

    Rastrigin function losses for . by Shikun Chen (14625352)

    Published 2025
    “…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
  17. 297

    Rastrigin function losses for . by Shikun Chen (14625352)

    Published 2025
    “…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
  18. 298

    Rosenbrock function losses for . by Shikun Chen (14625352)

    Published 2025
    “…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
  19. 299

    Flow chart diagram of quantum hash function. by Sultan H. Almotiri (14029251)

    Published 2024
    “…Our study addresses five major components of the quantum method to overcome these challenges: lattice-based cryptography, fully homomorphic algorithms, quantum key distribution, quantum hash functions, and blind quantum algorithms. …”
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