Search Results for author: Puoya Tabaghi

Found 6 papers, 1 papers with code

Highly Scalable and Provably Accurate Classification in Poincare Balls

1 code implementation8 Sep 2021 Eli Chien, Chao Pan, Puoya Tabaghi, Olgica Milenkovic

For hierarchical data, the space of choice is a hyperbolic space since it guarantees low-distortion embeddings for tree-like structures.

Classification Time Series

Linear Classifiers in Product Space Forms

no code implementations19 Feb 2021 Puoya Tabaghi, Eli Chien, Chao Pan, Jianhao Peng, Olgica Milenković

Embedding methods for product spaces are powerful techniques for low-distortion and low-dimensional representation of complex data structures.

On Procrustes Analysis in Hyperbolic Space

no code implementations7 Feb 2021 Puoya Tabaghi, Ivan Dokmanic

Congruent Procrustes analysis aims to find the best matching between two point sets through rotation, reflection and translation.

Translation

Geometry of Similarity Comparisons

no code implementations17 Jun 2020 Puoya Tabaghi, Jianhao Peng, Olgica Milenkovic, Ivan Dokmanić

To study this question, we introduce the notions of the \textit{ordinal capacity} of a target space form and \emph{ordinal spread} of the similarity measurements.

Hyperbolic Distance Matrices

no code implementations18 May 2020 Puoya Tabaghi, Ivan Dokmanić

Hyperbolic space is a natural setting for mining and visualizing data with hierarchical structure.

Hierarchical structure

Learning Schatten--von Neumann Operators

no code implementations29 Jan 2019 Puoya Tabaghi, Maarten de Hoop, Ivan Dokmanić

We study the learnability of a class of compact operators known as Schatten--von Neumann operators.

Learning Theory

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