2 citations · 4 across the 5 of their papers we have counts for
8 papers
HyperAid: Denoising in hyperbolic spaces for tree-fitting and hierarchical clustering
Eli Chien, Puoya Tabaghi, Olgica Milenkovic
The problem of fitting distances by tree-metrics has received significant attention in the theoretical computer science and machine learning communities alike, due to many applicat…
Provably Accurate and Scalable Linear Classifiers in Hyperbolic Spaces
Chao Pan, Eli Chien, Puoya Tabaghi +2
Many high-dimensional practical data sets have hierarchical structures induced by graphs or time series. Such data sets are hard to process in Euclidean spaces and one often seeks…
Highly Scalable and Provably Accurate Classification in Poincare Balls
Eli Chien, Chao Pan, Puoya Tabaghi +1
Many high-dimensional and large-volume data sets of practical relevance have hierarchical structures induced by trees, graphs or time series. Such data sets are hard to process in…
On Procrustes Analysis in Hyperbolic Space
Puoya Tabaghi, Ivan Dokmanic
Congruent Procrustes analysis aims to find the best matching between two point sets through rotation, reflection and translation. We formulate the Procrustes problem for hyperbolic…
Hyperbolic Distance Matrices
Puoya Tabaghi, Ivan Dokmanić
Hyperbolic space is a natural setting for mining and visualizing data with hierarchical structure. In order to compute a hyperbolic embedding from comparison or similarity informat…
Real Polynomial Gram Matrices Without Real Spectral Factors
Puoya Tabaghi, Ivan Dokmanić
It is well known that a non-negative definite polynomial matrix (a polynomial Gramian) can be written as a product of its polynomial spectral factors, .…