cuSLINK: Single-linkage Agglomerative Clustering on the GPU

1 code implementation • 28 Jun 2023 • Corey J. Nolet, Divye Gala, Alex Fender, Mahesh Doijade, Joe Eaton, Edward Raff, John Zedlewski, Brad Rees, Tim Oates

In this paper, we propose cuSLINK, a novel and state-of-the-art reformulation of the SLINK algorithm on the GPU which requires only $O(Nk)$ space and uses a parameter $k$ to trade off space and time.

Clustering graph construction

GPU Semiring Primitives for Sparse Neighborhood Methods

2 code implementations • 13 Apr 2021 • Corey J. Nolet, Divye Gala, Edward Raff, Joe Eaton, Brad Rees, John Zedlewski, Tim Oates

High-performance primitives for mathematical operations on sparse vectors must deal with the challenges of skewed degree distributions and limits on memory consumption that are typically not issues in dense operations.

BIG-bench Machine Learning Information Retrieval +1

Bringing UMAP Closer to the Speed of Light with GPU Acceleration

1 code implementation • 1 Aug 2020 • Corey J. Nolet, Victor Lafargue, Edward Raff, Thejaswi Nanditale, Tim Oates, John Zedlewski, Joshua Patterson

The Uniform Manifold Approximation and Projection (UMAP) algorithm has become widely popular for its ease of use, quality of results, and support for exploratory, unsupervised, supervised, and semi-supervised learning.

Domain Stylization: A Strong, Simple Baseline for Synthetic to Real Image Domain Adaptation

no code implementations • 24 Jul 2018 • Aysegul Dundar, Ming-Yu Liu, Ting-Chun Wang, John Zedlewski, Jan Kautz

Deep neural networks have largely failed to effectively utilize synthetic data when applied to real images due to the covariate shift problem.

Domain Adaptation object-detection +5