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stat.ML2024
On Probabilistic Embeddings in Optimal Dimension Reduction
Ryan Murray, Adam Pickarski
Dimension reduction algorithms are a crucial part of many data science pipelines, including data exploration, feature creation and selection, and denoising. Despite their wide util…
stat.ML2023
Dirichlet Active Learning
Kevin Miller, Ryan Murray
This work introduces Dirichlet Active Learning (DiAL), a Bayesian-inspired approach to the design of active learning algorithms. Our framework models feature-conditional class prob…