
Local Algorithms for Finding Densely Connected Clusters
Local graph clustering is an important algorithmic technique for analysi...
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Optimized RateProfiling for PAC Codes
The polarizationadjusted convolutional (PAC) codes concatenate the pola...
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EndtoEnd Sequential Sampling and Reconstruction for MR Imaging
Accelerated MRI shortens acquisition time by subsampling in the measurem...
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HigherOrder Spectral Clustering of Directed Graphs
Clustering is an important topic in algorithms, and has a number of appl...
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Deep Probabilistic Imaging: Uncertainty Quantification and Multimodal Solution Characterization for Computational Imaging
Computational image reconstruction algorithms generally produce a single...
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DecisionAware Conditional GANs for Time Series Data
We introduce the decisionaware timeseries conditional generative adver...
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Augmenting the Algebraic Connectivity of Graphs
For any undirected graph G=(V,E) and a set E_W of candidate edges with E...
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Learning SpatialSpectral Prior for SuperResolution of Hyperspectral Imagery
Recently, single gray/RGB image superresolution reconstruction task has...
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FullyDynamic Graph Sparsifiers Against an Adaptive Adversary
Designing dynamic graph algorithms against an adaptive adversary is a ma...
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Learning a Probabilistic Strategy for Computational Imaging Sensor Selection
Optimized sensing is important for computational imaging in lowresource...
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Hermitian matrices for clustering directed graphs: insights and applications
Graph clustering is a basic technique in machine learning, and has wides...
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Hermitian Laplacians and a Cheeger inequality for the Max2Lin problem
We study spectral approaches for the MAX2LIN(k) problem, in which we a...
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Temporal Human Action Segmentation via Dynamic Clustering
We present an effective dynamic clustering algorithm for the task of tem...
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Distributed Graph Clustering and Sparsification
Graph clustering is a fundamental computational problem with a number of...
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