Search Results for author: Jeremy G. Hoskins

Found 2 papers, 2 papers with code

Learning Networks from Random Walk-Based Node Similarities

1 code implementation23 Jan 2018 Jeremy G. Hoskins, Cameron Musco, Christopher Musco, Charalampos E. Tsourakakis

In this work we consider a privacy threat to a social network in which an attacker has access to a subset of random walk-based node similarities, such as effective resistances (i. e., commute times) or personalized PageRank scores.

Anomaly Detection Graph Clustering +2

Efficient Algorithms for t-distributed Stochastic Neighborhood Embedding

8 code implementations25 Dec 2017 George C. Linderman, Manas Rachh, Jeremy G. Hoskins, Stefan Steinerberger, Yuval Kluger

t-distributed Stochastic Neighborhood Embedding (t-SNE) is a method for dimensionality reduction and visualization that has become widely popular in recent years.

Dimensionality Reduction

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