57 citations · 245 across the 48 of their papers we have counts for
11 papers · 1 filter
Hierarchical Clustering for Euclidean Data
Moses Charikar, Vaggos Chatziafratis, Rad Niazadeh +1
Recent works on Hierarchical Clustering (HC), a well-studied problem in exploratory data analysis, have focused on optimizing various objective functions for this problem under arb…
Recovery Guarantees for Quadratic Tensors with Sparse Observations
Hongyang R. Zhang, Vatsal Sharan, Moses Charikar +1
We consider the tensor completion problem of predicting the missing entries of a tensor. The commonly used CP model has a triple product form, but an alternate family of quadratic…
A sampling framework for counting temporal motifs
Paul Liu, Austin Benson, Moses Charikar
Pattern counting in graphs is fundamental to network science tasks, and there are many scalable methods for approximating counts of small patterns, often called motifs, in large gr…
Local Density Estimation in High Dimensions
Xian Wu, Moses Charikar, Vishnu Natchu
An important question that arises in the study of high dimensional vector representations learned from data is: given a set of vectors and a query , estimate the n…
Hashing-Based-Estimators for Kernel Density in High Dimensions
Moses Charikar, Paris Siminelakis
Given a set of points and a kernel , the Kernel Density Estimate at a point is defined as $\mathrm{KDE}_{P}(x)=\frac{1}{|P|}\sum_{…
Hierarchical Clustering better than Average-Linkage
Moses Charikar, Vaggos Chatziafratis, Rad Niazadeh
Hierarchical Clustering (HC) is a widely studied problem in exploratory data analysis, usually tackled by simple agglomerative procedures like average-linkage, single-linkage or co…