136 citations · 908 across the 46 of their papers we have counts for
3 papers · 1 filter
Generative Discrete Event Process Simulation for Hidden Markov Models to Predict Competitor Time-to-Market
Nandakishore Santhi, Stephan Eidenbenz, Brian Key +1
We study the challenge of predicting the time at which a competitor product, such as a novel high-capacity EV battery or a new car model, will be available to customers; as new inf…
Generating Hidden Markov Models from Process Models Through Nonnegative Tensor Factorization
Erik Skau, Andrew Hollis, Stephan Eidenbenz +2
Monitoring of industrial processes is a critical capability in industry and in government to ensure reliability of production cycles, quick emergency response, and national securit…
BB-ML: Basic Block Performance Prediction using Machine Learning Techniques
Hamdy Abdelkhalik, Shamminuj Aktar, Yehia Arafa +8
Recent years have seen the adoption of Machine Learning (ML) techniques to predict the performance of large-scale applications, mostly at a coarse level. In contrast, we propose to…