Fuzzy Logic on Quantum Annealers

Article Multidisciplinary Sciences

QUBO formulations for training machine learning models

Prasanna Date et al.

Summary: Training machine learning models on classical computers is time and compute intensive, while leveraging quantum computing, particularly adiabatic quantum computers, may offer faster solutions. By formulating machine learning problems as QUBO problems for adiabatic quantum computers, efficiency gains can be achieved. The computational complexities of these formulations are shown to be better or equivalent to classical approaches.

SCIENTIFIC REPORTS (2021)

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Article Quantum Science & Technology

Grover Adaptive Search for Constrained Polynomial Binary Optimization

Austin Gilliam et al.

Summary: This paper discusses using Grover Adaptive Search (GAS) to solve Constrained Polynomial Binary Optimization (CPBO) problems, particularly Quadratic Unconstrained Binary Optimization (QUBO) problems, by developing efficient oracles, demonstrating potential speed-up in combinatorial optimization and QUBO, and applying to higher-degree polynomial objective functions and constrained optimization problems.

QUANTUM (2021)

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Article Computer Science, Information Systems

A Novel Quantum-Inspired Fuzzy Based Neural Network for Data Classification

Om Prakash Patel et al.

Summary: This paper introduces a novel learning model called Q-FNN that incorporates quantum-inspired and fuzzy c-means clustering concepts, achieving superior performance on 15 real-world benchmark datasets.

IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING (2021)

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Article Computer Science, Artificial Intelligence