首页|Indian Institute of Technology Madras Researchers Publish New Study Findings on Support Vector Machines [Pneumonia detection by binary classification: classical, quantum, and hybrid approaches for support vector machine (SVM)]
Indian Institute of Technology Madras Researchers Publish New Study Findings on Support Vector Machines [Pneumonia detection by binary classification: classical, quantum, and hybrid approaches for support vector machine (SVM)]
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on . According to news reporting from Chennai, India, by NewsRx journalists, research stated, “Early diagnosis of pneumonia is crucial to increase the chances ofsurvival and reduce the recovery time of the patient.”Our news correspondents obtained a quote from the research from Indian Institute of TechnologyMadras: “Chest X-ray images, the most widely used method in practice, are challenging to classify. Ouraim is to develop a machine learning tool that can accurately classify images as belonging to normal orinfected individuals. A support vector machine (SVM) is attractive because binary classification can berepresented as an optimization problem, in particular as a Quadratic Unconstrained Binary Optimization(QUBO) model, which, in turn, maps naturally to an Ising model, thereby making annealing-classical,quantum, and hybrid-an attractive approach to explore. In this study, we offer a comparison betweendifferent methods: (1) a classical state-of-the-art implementation of SVM (LibSVM); (2) solving SVM witha classical solver (Gurobi), with and without decomposition; (3) solving SVM with simulated annealing; (4)solving SVM with quantum annealing (D-Wave); and (5) solving SVM using Graver Augmented Multi-seedAlgorithm (GAMA). GAMA is tried with several different numbers of Graver elements and a number ofseeds using both simulating annealing and quantum annealing.”
Indian Institute of Technology MadrasChennaiIndiaAsiaEmerging TechnologiesMachine LearningSupport Vector MachinesVector Machines
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