Analysis of quantum machine learning algorithms in noisy channels for classification tasks in the iot extreme environment
SK Satpathy, V Vibhu, BK Behera… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
By 2050, there will be a 50% rise in energy demand, and existing natural and renewable
resources will be under extreme scrutiny. Optimizing current power generation and …
resources will be under extreme scrutiny. Optimizing current power generation and …
Quantum K-means clustering method for detecting heart disease using quantum circuit approach
SS Kavitha, N Kaulgud - Soft Computing, 2023 - Springer
The development of noisy intermediate-scale quantum computers is expected to signify the
potential advantages of quantum computing over classical computing. This paper focuses …
potential advantages of quantum computing over classical computing. This paper focuses …
[HTML][HTML] Quantum clustering with k-means: A hybrid approach
Quantum computing, based on quantum theory, holds great promise as an advanced
computational paradigm for achieving fast computations. Quantum algorithms are expected …
computational paradigm for achieving fast computations. Quantum algorithms are expected …
Quantum computing to study cloud turbulence properties
The analysis and investigation of the data obtained from Direct Numerical (DNS) simulation
of droplet dynamics in cloud turbulence is a complex and time-consuming task when …
of droplet dynamics in cloud turbulence is a complex and time-consuming task when …
Practical quantum k-means clustering: Performance analysis and applications in energy grid classification
In this work, we aim to solve a practical use-case of unsupervised clustering that has
applications in predictive maintenance in the energy operations sector using quantum …
applications in predictive maintenance in the energy operations sector using quantum …
Quantum machine learning: Current state and challenges
M Avramouli, I Savvas, G Garani… - Proceedings of the 25th …, 2021 - dl.acm.org
In recent years, machine learning has penetrated a large part of our daily lives, which
creates special challenges and impressive progress in this area. Nevertheless, as the …
creates special challenges and impressive progress in this area. Nevertheless, as the …
Quarta: quantum supervised and unsupervised learning for binary classification in domain-incremental learning
C Loglisci, D Malerba, S Pascazio - Quantum Machine Intelligence, 2024 - Springer
Quantum machine learning recently gained prominence due to the promise of quantum
computers in solving machine learning problems that are intractable on a classical …
computers in solving machine learning problems that are intractable on a classical …
Quantum machine learning algorithms for diagnostic applications: a review
SS Pophale, A Gadekar - International virtual conference on industry, 2021 - Springer
Big data analytics is a huge information investigation in the utilization of cutting edge
scientific procedures against extremely enormous, various in-formational collections that …
scientific procedures against extremely enormous, various in-formational collections that …
BibPat: Quantum K-means Clustering with Incremental Enhancement
S Deshmukh, P Mulay - Recent Patents on Engineering, 2024 - benthamdirect.com
One of the main areas of study within the broader paradigm of quantum machine learning is
quantum clustering (QC). Considering the potential time and cost savings that solutions to …
quantum clustering (QC). Considering the potential time and cost savings that solutions to …
Quantum Machine Learning Approaches
M Poobala, GK Natarajan, I Shanmugam… - Quantum Machine …, 2024 - taylorfrancis.com
The rise of machine learning algorithms in multidisciplinary areas is inevitable. Quantum
computers are a significant recent area of development where complex algorithms can be …
computers are a significant recent area of development where complex algorithms can be …