Abstract 3D instance segmentation is fundamental to geometric understanding of the world
around us. Existing methods for instance segmentation of 3D scenes rely on supervision …

In recent decades, spectral clustering has found widespread applications in various real-
world scenarios, showcasing its effectiveness. Traditional spectral clustering typically follows …

In semiconductor industry, various wafer defect patterns represent different causes of
manufacturing failures. Identification of specific defect patterns is important to wafer …

Finding brain tumors is a crucial step in medical diagnosis that can have a big impact on
how patients turn out. Conventional detection techniques can be laborious and demand a lot …

Many existing graph-clustering methods get results in a two-stage manner, including
constructing a graph from data and partitioning it. It always leads to sub-optimal …

We present two practical improvement techniques for unsupervised segmentation learning.
These techniques address limitations in the resolution and accuracy of predicted …

Ginzburg--Landau (GL) functionals on graphs, which are relaxations of graph-cut functionals
on graphs, have yielded a variety of insights in image segmentation and graph clustering. In …

Given an undirected, weighted $ n $-vertex graph $ G=(V, E, w) $, a Gomory-Hu tree $ T $ is
a weighted tree on $ V $ such that for any pair of distinct vertices $ s, t\in V $, the Min-$ s …

Local grouping is a commonly used technique to scale application size in machine learning
domains, such as image segmentation, graph representation learning, and multidimensional …

Abstract In the 2-Club Cluster Vertex Deletion (resp., 2-Club Cluster Edge Deletion) problem
the input is a graph G and an integer k, and the goal is to decide whether there is a set of at …