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Found 2 papers, 1 papers with code
Risk-Aware Scene Sampling for Dynamic Assurance of Autonomous Systems
Our samplers of RNS and GBO sampled a higher percentage of high-risk scenes of 83% and 92%, compared to 56%, 66% and 71% of the grid, random and Halton samplers, respectively.
Stratum: A Serverless Framework for Lifecycle Management of Machine Learning based Data Analytics Tasks
With the proliferation of machine learning (ML) libraries and frameworks, and the programming languages that they use, along with operations of data loading, transformation, preparation and mining, ML model development is becoming a daunting task.
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