2.1k citations · 4.3k across the 48 of their papers we have counts for
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Efficient Algorithms for t-distributed Stochastic Neighborhood Embedding
George C. Linderman, Manas Rachh, Jeremy G. Hoskins +2
t-distributed Stochastic Neighborhood Embedding (t-SNE) is a method for dimensionality reduction and visualization that has become widely popular in recent years. Efficient impleme…
Randomized Near Neighbor Graphs, Giant Components, and Applications in Data Science
George C. Linderman, Gal Mishne, Yuval Kluger +1
If we pick random points uniformly in and connect each point to its nearest neighbors, then it is well known that there exists a giant connected component with hi…
Data-Driven Tree Transforms and Metrics
Gal Mishne, Ronen Talmon, Israel Cohen +2
We consider the analysis of high dimensional data given in the form of a matrix with columns consisting of observations and rows consisting of features. Often the data is such that…
Mahalanonbis Distance Informed by Clustering
Almog Lahav, Ronen Talmon, Yuval Kluger
A fundamental question in data analysis, machine learning and signal processing is how to compare between data points. The choice of the distance metric is specifically challenging…
Unsupervised Ensemble Regression
Omer Dror, Boaz Nadler, Erhan Bilal +1
Consider a regression problem where there is no labeled data and the only observations are the predictions of experts over many samples . With no knowle…