skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


This content will become publicly available on July 8, 2026

Title: All-Subsets Important Separators with Applications to Sample Sets, Balanced Separators and Vertex Sparsifiers in Directed Graphs
Award ID(s):
2238138
PAR ID:
10599135
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
Schloss Dagstuhl-Leibniz-Zentrum für Informatik
Date Published:
ISSN:
1868-8969
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. We develop the first polynomial-time algorithm for co-training of homogeneous linear separators under \em weak dependence, a relaxation of the condition of independence given the label. Our algorithm learns from purely unlabeled data, except for a single labeled example to break symmetry of the two classes, and works for any data distribution having an inverse-polynomial margin and with center of mass at the origin. 
    more » « less