Abstract
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."
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