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Exploiting variable task granularities for scalable and efficient parallel graph analytics
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Graph-based models and transforms for signal/data processing with applications to video coding
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Dynamic graph analytics for cyber systems security applications
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Graph embedding algorithms for attributed and temporal graphs
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Human activity analysis with graph signal processing techniques
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Lifting transforms on graphs: theory and applications
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Probabilistic methods and randomized algorithms
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Sampling theory for graph signals with applications to semi-supervised learning
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Disparity estimation from multi-view images and video: graph models and algorithms
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Learning the geometric structure of high dimensional data using the Tensor Voting Graph
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Network structures: graph theory, statistics, and neuroscience applications
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Efficient graph processing with graph semantics aware intelligent storage
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Estimation of graph Laplacian and covariance matrices
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Physics-aware graph networks for spatiotemporal physical systems
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Efficient transforms for graph signals with applications to video coding
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Compression of signal on graphs with the application to image and video coding
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Speeding up distributed constraint optimization search algorithms
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Architecture design and algorithmic optimizations for accelerating graph analytics on FPGA
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QoS-aware algorithm design for distributed systems
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Speeding up path planning on state lattices and grid graphs by exploiting freespace structure
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Online learning algorithms for network optimization with unknown variables
De novo peptide sequencing and spectral alignment algorithm via tandem mass spectrometry
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Novel algorithms for large scale supervised and one class learning
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Realistic modeling of wireless communication graphs for the design of efficient sensor network routing protocols
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Improving machine learning algorithms via efficient data relevance discovery
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