Researchers have created a taxonomy and outlined steps that developers can take to design features in machine-learning models that are easier for decision-makers to understand. Explanation methods ...
Modern NoC (Network-on-Chip) is built of complex functional blocks, such as packet switches and protocol converters. PPA (performance/power/area) estimates for these ...
By using reinforcement learning, researchers train virtual agent to determine the best time to administer medication based on ...
eWeek content and product recommendations are editorially independent. We may make money when you click on links to our partners. Learn More Machine learning (ML) uses advanced mathematical models ...
Explainable machine learning is a sub-discipline of artificial intelligence (AI) and machine learning that attempts to summarize how machine learning systems make decisions. Summarizing how machine ...
To identify and evaluate candidate materials, process engineers must analyze an enormous amount of data. Bulk properties like ...
After talking to machine learning and infrastructure engineers at major Internet companies across the US, Europe, and China, two groups of companies emerged. One group has invested hundreds of ...
Explanation methods that help users understand and trust machine-learning models often describe how much certain features used in the model contribute to its prediction. For example, if a model ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback