Search Results for author: He Sun

Found 15 papers, 5 papers with code

Local Algorithms for Finding Densely Connected Clusters

1 code implementation9 Jun 2021 Peter Macgregor, He Sun

Local graph clustering is an important algorithmic technique for analysing massive graphs, and has been widely applied in many research fields of data science.

Graph Clustering

End-to-End Sequential Sampling and Reconstruction for MR Imaging

1 code implementation13 May 2021 Tianwei Yin, Zihui Wu, He Sun, Adrian V. Dalca, Yisong Yue, Katherine L. Bouman

In this paper, we leverage the sequential nature of MRI measurements, and propose a fully differentiable framework that jointly learns a sequential sampling policy simultaneously with a reconstruction strategy.

Higher-Order Spectral Clustering of Directed Graphs

no code implementations NeurIPS 2020 Steinar Laenen, He Sun

Clustering is an important topic in algorithms, and has a number of applications in machine learning, computer vision, statistics, and several other research disciplines.

Graph Clustering

Deep Probabilistic Imaging: Uncertainty Quantification and Multi-modal Solution Characterization for Computational Imaging

1 code implementation27 Oct 2020 He Sun, Katherine L. Bouman

In this paper, we propose a variational deep probabilistic imaging approach to quantify reconstruction uncertainty.

Image Reconstruction

Decision-Aware Conditional GANs for Time Series Data

no code implementations26 Sep 2020 He Sun, Zhun Deng, Hui Chen, David C. Parkes

We introduce the decision-aware time-series conditional generative adversarial network (DAT-CGAN) as a method for time-series generation.

Time Series

High-Contrast Integral Field Spectrograph (HCIFS): multi-spectral wavefront control and reduced-dimensional system identification

no code implementations19 May 2020 He Sun, Alexei Goun, Susan Redmond, Michael Galvin, Tyler Groff, Maxime Rizzo, N. Jeremy Kasdin

Any high-contrast imaging instrument in a future large space-based telescope will include an integral field spectrograph (IFS) for measuring broadband starlight residuals and characterizing the exoplanet's atmospheric spectrum.

Instrumentation and Methods for Astrophysics Optics

Learning Spatial-Spectral Prior for Super-Resolution of Hyperspectral Imagery

2 code implementations18 May 2020 Junjun Jiang, He Sun, Xian-Ming Liu, Jiayi Ma

Recently, single gray/RGB image super-resolution reconstruction task has been extensively studied and made significant progress by leveraging the advanced machine learning techniques based on deep convolutional neural networks (DCNNs).

Hyperspectral Image Super-Resolution Image Super-Resolution

Learning a Probabilistic Strategy for Computational Imaging Sensor Selection

no code implementations23 Mar 2020 He Sun, Adrian V. Dalca, Katherine L. Bouman

In this paper, we demonstrate the approach in the context of a very-long-baseline-interferometry (VLBI) array design task, where sensor correlations and atmospheric noise present unique challenges.

Hermitian matrices for clustering directed graphs: insights and applications

no code implementations6 Aug 2019 Mihai Cucuringu, Huan Li, He Sun, Luca Zanetti

Graph clustering is a basic technique in machine learning, and has widespread applications in different domains.

Graph Clustering Stochastic Block Model

Temporal Human Action Segmentation via Dynamic Clustering

1 code implementation15 Mar 2018 Yan Zhang, He Sun, Siyu Tang, Heiko Neumann

We present an effective dynamic clustering algorithm for the task of temporal human action segmentation, which has comprehensive applications such as robotics, motion analysis, and patient monitoring.

Action Segmentation

Distributed Graph Clustering and Sparsification

no code implementations3 Nov 2017 He Sun, Luca Zanetti

Graph clustering is a fundamental computational problem with a number of applications in algorithm design, machine learning, data mining, and analysis of social networks.

Data Structures and Algorithms Distributed, Parallel, and Cluster Computing

An SDP-Based Algorithm for Linear-Sized Spectral Sparsification

no code implementations27 Feb 2017 Yin Tat Lee, He Sun

Noticing that $\Omega(m)$ time is needed for any algorithm to construct a spectral sparsifier and a spectral sparsifier of $G$ requires $\Omega(n)$ edges, a natural question is to investigate, for any constant $\varepsilon$, if a $(1+\varepsilon)$-spectral sparsifier of $G$ with $O(n)$ edges can be constructed in $\tilde{O}(m)$ time, where the $\tilde{O}$ notation suppresses polylogarithmic factors.

Communication-Optimal Distributed Clustering

no code implementations NeurIPS 2016 Jiecao Chen, He Sun, David P. Woodruff, Qin Zhang

We would like the quality of the clustering in the distributed setting to match that in the centralized setting for which all the data resides on a single site.

Distributed Graph Clustering by Load Balancing

no code implementations18 Jul 2016 He Sun, Luca Zanetti

In this paper we present a simple and distributed algorithm for graph clustering: for a wide class of graphs that are characterised by a strong cluster-structure, our algorithm finishes in a poly-logarithmic number of rounds, and recovers a partition of the graph close to an optimal partition.

Distributed Computing Graph Clustering

Partitioning Well-Clustered Graphs: Spectral Clustering Works!

no code implementations7 Nov 2014 Richard Peng, He Sun, Luca Zanetti

In this paper we study variants of the widely used spectral clustering that partitions a graph into k clusters by (1) embedding the vertices of a graph into a low-dimensional space using the bottom eigenvectors of the Laplacian matrix, and (2) grouping the embedded points into k clusters via k-means algorithms.

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