Search Results for author: Chao Pan

Found 7 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

You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks

no code implementations24 Jun 2021 Eli Chien, Chao Pan, Jianhao Peng, Olgica Milenkovic

We propose AllSet, a new hypergraph neural network paradigm that represents a highly general framework for (hyper)graph neural networks and for the first time implements hypergraph neural network layers as compositions of two multiset functions that can be efficiently learned for each task and each dataset.

Node Classification

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.

Spatio-Temporal Graph Scattering Transform

no code implementations ICLR 2021 Chao Pan, Siheng Chen, Antonio Ortega

Although spatio-temporal graph neural networks have achieved great empirical success in handling multiple correlated time series, they may be impractical in some real-world scenarios due to a lack of sufficient high-quality training data.

Time Series

Image processing in DNA

no code implementations22 Oct 2019 Chao Pan, S. M. Hossein Tabatabaei Yazdi, S Kasra Tabatabaei, Alvaro G. Hernandez, Charles Schroeder, Olgica Milenkovic

The main obstacles for the practical deployment of DNA-based data storage platforms are the prohibitively high cost of synthetic DNA and the large number of errors introduced during synthesis.

Image Inpainting Quantization

Query K-means Clustering and the Double Dixie Cup Problem

no code implementations NeurIPS 2018 I Chien, Chao Pan, Olgica Milenkovic

We consider the problem of approximate $K$-means clustering with outliers and side information provided by same-cluster queries and possibly noisy answers.

Group Additive Structure Identification for Kernel Nonparametric Regression

no code implementations NeurIPS 2017 Chao Pan, Michael Zhu

The additive model is one of the most popularly used models for high dimensional nonparametric regression analysis.

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