47 citations · 62 across the 6 of their papers we have counts for
4 papers · 1 filter
Batch Active Learning at Scale
Gui Citovsky, Giulia DeSalvo, Claudio Gentile +4
The ability to train complex and highly effective models often requires an abundance of training data, which can easily become a bottleneck in cost, time, and computational resourc…
Scaling Hierarchical Agglomerative Clustering to Billion-sized Datasets
Baris Sumengen, Anand Rajagopalan, Gui Citovsky +6
Hierarchical Agglomerative Clustering (HAC) is one of the oldest but still most widely used clustering methods. However, HAC is notoriously hard to scale to large data sets as the…
Online Hierarchical Clustering Approximations
Aditya Krishna Menon, Anand Rajagopalan, Baris Sumengen +3
Hierarchical clustering is a widely used approach for clustering datasets at multiple levels of granularity. Despite its popularity, existing algorithms such as hierarchical agglom…
Flattening a Hierarchical Clustering through Active Learning
Fabio Vitale, Anand Rajagopalan, Claudio Gentile
We investigate active learning by pairwise similarity over the leaves of trees originating from hierarchical clustering procedures. In the realizable setting, we provide a full cha…