首页|New Machine Learning Study Findings Recently Were Published by Researchers at Un iversity of California San Diego (UCSD) (Optimized Early Prediction of Business Processes with Hyperdimensional Computing)
New Machine Learning Study Findings Recently Were Published by Researchers at Un iversity of California San Diego (UCSD) (Optimized Early Prediction of Business Processes with Hyperdimensional Computing)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on ar tificial intelligence. According to news reporting out of La Jolla, California, by NewsRx editors, research stated, "There is a growing interest in the early pr ediction of outcomes in ongoing business processes." Funders for this research include Center For Processing With Intelligent Storage And Memory; Cocosys, Centers in Jump 2.0; Darpa; Nsf. Our news editors obtained a quote from the research from University of Californi a San Diego (UCSD): "Predictive process monitoring distills knowledge from the s equence of event data generated and stored during the execution of processes and trains models on this knowledge to predict outcomes of ongoing processes. Howev er, most state-of-the-art methods require the training of complex and inefficien t machine learning models and hyper-parameter optimization as well as numerous i nput datato achieve high performance. In this paper, we present a novel approac h based on Hyperdimensional Computing (HDC) for predicting the outcome of ongoin g processes before their completion. We highlight its simplicity, efficiency, an d high performance while utilizing only a subset of the input data, which helps in achieving a lower memory demand and faster and more effective corrective meas ures. We evaluate our proposed method on four publicly available datasets with atotal of 12 binary prediction tasks."
University of California San Diego (UCSD )La JollaCaliforniaUnited StatesNorth and Central AmericaCyborgsEmer ging TechnologiesMachine Learning
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