Description
INTRODUCTION
- Quantum machine learning is the integration of quantum algorithms within machine learning programs.
Quantum Machine Learning Presentation Report
Page Length: 42
Covered Topic :
- Introduction
- Linear algebra simulation with quantum amplitudes
- Quantum Computing
- Quantum Machine Learning
- Grover based algorithms for Quantum Machine Learning
- Grover algorithm
- Grover algorithm, qRAM version
- Random Access Memory
- Quantum Random Access Memory (qRAM)
- Grover Algorithm and qRAM
- Type of Complexity Grover Algorithm and qRAM
- Extended Grover Algorithm and qRAM
- Machine Learning
- Nearest-Neighbor Method for Supervised Learning
- (Unsupervised) Machine Learning
- Quantum Basic Linear Algebra Subroutines (qBLAS) AKA HHL
- qBLAS Caveats
- Quantum tunneling versus thermalization
- HP’s Dot-Product Engine for Neuromorphic Computing
- Compute Power, or Data Storage & Movement:Which one is more important in Machine Learning?
- Adiabatic quantum computation (Quantum Annealing)
- Optimization, an important ingredient of Machine Learning
- Conclusion
- Challenges & Future Work
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