42 citations · 74 across the 5 of their papers we have counts for
5 papers
Masked Topology Modeling for Self-Supervised Learning on Parametric CAD
Heinrich Jiang, Jennifer Jang
Computer aided design (CAD) is ubiquitous: virtually any modern object was designed using editable CAD tools. However, with the shortage of available CAD datasets in its native edi…
MeanShift++: Extremely Fast Mode-Seeking With Applications to Segmentation and Object Tracking
Jennifer Jang, Heinrich Jiang
MeanShift is a popular mode-seeking clustering algorithm used in a wide range of applications in machine learning. However, it is known to be prohibitively slow, with quadratic run…
Faster DBSCAN via subsampled similarity queries
Heinrich Jiang, Jennifer Jang, Jakub Łącki
DBSCAN is a popular density-based clustering algorithm. It computes the -neighborhood graph of a dataset and uses the connected components of the high-degree nodes to decide the…
DBSCAN++: Towards fast and scalable density clustering
Jennifer Jang, Heinrich Jiang
DBSCAN is a classical density-based clustering procedure with tremendous practical relevance. However, DBSCAN implicitly needs to compute the empirical density for each sample poin…
Quickshift++: Provably Good Initializations for Sample-Based Mean Shift
Heinrich Jiang, Jennifer Jang, Samory Kpotufe
We provide initial seedings to the Quick Shift clustering algorithm, which approximate the locally high-density regions of the data. Such seedings act as more stable and expressive…