8 citations · 11 across the 4 of their papers we have counts for
4 papers
PACSET (Packed Serialized Trees): Reducing Inference Latency for Tree Ensemble Deployment
Meghana Madhyastha, Kunal Lillaney, James Browne +2
We present methods to serialize and deserialize tree ensembles that optimize inference latency when models are not already loaded into memory. This arises whenever models are large…
Geodesic Learning via Unsupervised Decision Forests
Meghana Madhyastha, Percy Li, James Browne +4
Geodesic distance is the shortest path between two points in a Riemannian manifold. Manifold learning algorithms, such as Isomap, seek to learn a manifold that preserves geodesic d…
Forest Packing: Fast, Parallel Decision Forests
James Browne, Tyler M. Tomita, Disa Mhembere +2
Machine learning has an emerging critical role in high-performance computing to modulate simulations, extract knowledge from massive data, and replace numerical models with efficie…
Sparse Projection Oblique Randomer Forests
Tyler M. Tomita, James Browne, Cencheng Shen +8
Decision forests, including Random Forests and Gradient Boosting Trees, have recently demonstrated state-of-the-art performance in a variety of machine learning settings. Decision…