17 citations · 33 across the 7 of their papers we have counts for
5 papers · 1 filter
Scalable Hierarchical Clustering with Tree Grafting
Nicholas Monath, Ari Kobren, Akshay Krishnamurthy +2
We introduce Grinch, a new algorithm for large-scale, non-greedy hierarchical clustering with general linkage functions that compute arbitrary similarity between two point sets. Th…
Optimal Transport-based Alignment of Learned Character Representations for String Similarity
Derek Tam, Nicholas Monath, Ari Kobren +3
String similarity models are vital for record linkage, entity resolution, and search. In this work, we present STANCE --a learned model for computing the similarity of two strings.…
Supervised Hierarchical Clustering with Exponential Linkage
Nishant Yadav, Ari Kobren, Nicholas Monath +1
In supervised clustering, standard techniques for learning a pairwise dissimilarity function often suffer from a discrepancy between the training and clustering objectives, leading…
Paper Matching with Local Fairness Constraints
Ari Kobren, Barna Saha, Andrew McCallum
Automatically matching reviewers to papers is a crucial step of the peer review process for venues receiving thousands of submissions. Unfortunately, common paper matching algorith…
Constructing High Precision Knowledge Bases with Subjective and Factual Attributes
Ari Kobren, Pablo Barrio, Oksana Yakhnenko +2
Knowledge bases (KBs) are the backbone of many ubiquitous applications and are thus required to exhibit high precision. However, for KBs that store subjective attributes of entitie…