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Found 3 papers, 2 papers with code
Talaria: Interactively Optimizing Machine Learning Models for Efficient Inference
On-device machine learning (ML) moves computation from the cloud to personal devices, protecting user privacy and enabling intelligent user experiences.
Neo: Generalizing Confusion Matrix Visualization to Hierarchical and Multi-Output Labels
The confusion matrix, a ubiquitous visualization for helping people evaluate machine learning models, is a tabular layout that compares predicted class labels against actual class labels over all data instances.
Uncertainty-Aware Principal Component Analysis
We present a technique to perform dimensionality reduction on data that is subject to uncertainty.
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