2 citations · 2 across the 3 of their papers we have counts for
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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…
You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks
Eli Chien, Chao Pan, Jianhao Peng +1
Hypergraphs are used to model higher-order interactions amongst agents and there exist many practically relevant instances of hypergraph datasets. To enable efficient processing of…
Linear Classifiers in Product Space Forms
Puoya Tabaghi, Chao Pan, Eli Chien +2
Embedding methods for product spaces are powerful techniques for low-distortion and low-dimensional representation of complex data structures. Here, we address the new problem of l…
Geometry of Similarity Comparisons
Puoya Tabaghi, Jianhao Peng, Olgica Milenkovic +1
Many data analysis problems can be cast as distance geometry problems in \emph{space forms} -- Euclidean, spherical, or hyperbolic spaces. Often, absolute distance measurements are…
Adaptive Universal Generalized PageRank Graph Neural Network
Eli Chien, Jianhao Peng, Pan Li +1
In many important graph data processing applications the acquired information includes both node features and observations of the graph topology. Graph neural networks (GNNs) are d…
Online Convex Matrix Factorization with Representative Regions
Abhishek Agarwal, Jianhao Peng, Olgica Milenkovic
Matrix factorization (MF) is a versatile learning method that has found wide applications in various data-driven disciplines. Still, many MF algorithms do not adequately scale with…