Quantum Machine Learning: Bridging Quantum Computing and Artificial Intelligence

EasyChair Preprint 12237

Abstract

In recent years, quantum computing has emerged as a promising paradigm, offering exponential speedups for certain computational tasks. Concurrently, AI techniques have revolutionized industries, enabling machines to learn from data and make intelligent decisions. QML integrates these advancements, leveraging quantum principles to enhance the capabilities of AI algorithms. Key to QML is the utilization of quantum algorithms and quantum-inspired techniques to process and analyze data. Quantum algorithms such as quantum annealing, quantum variational algorithms, and quantum tensor networks hold the potential to solve complex optimization and machine learning problems exponentially faster than classical counterparts.

Keyphrases: learning, machine, quantum

@booklet{EasyChair:12237,
  author    = {Kurez Oroy and Robert Jhon},
  title     = {Quantum Machine Learning: Bridging Quantum Computing and Artificial Intelligence},
  howpublished = {EasyChair Preprint 12237},
  year      = {EasyChair, 2024}}