4 papers · 1 filter
A Fast and Effective Method for Euclidean Anticlustering: The Assignment-Based-Anticlustering Algorithm
Philipp Baumann, Olivier Goldschmidt, Dorit S. Hochbaum +1
Anticlustering is an NP-hard combinatorial optimization problem that consists of partitioning a set of objects into equal-sized groups called anticlusters such that the objects in…
An Effective Flow-based Method for Positive-Unlabeled Learning: 2-HNC
Dorit Hochbaum, Torpong Nitayanont
In many scenarios of binary classification, only positive instances are provided in the training data, leaving the rest of the data unlabeled. This setup, known as positive-unlabel…
Confidence HNC: A Network Flow Technique for Binary Classification with Noisy Labels
Dorit Hochbaum, Torpong Nitayanont
We consider here a classification method that balances two objectives: large similarity within the samples in the cluster, and large dissimilarity between the cluster and its compl…
An algorithm for clustering with confidence-based must-link and cannot-link constraints
Philipp Baumann, Dorit S. Hochbaum
We study here the semi-supervised -clustering problem where information is available on whether pairs of objects are in the same or in different clusters. This information is ei…