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