
AliGraph: A Comprehensive Graph Neural Network Platform
An increasing number of machine learning tasks require dealing with larg...
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Penalized matrix decomposition for denoising, compression, and improved demixing of functional imaging data
Calcium imaging has revolutionized systems neuroscience, providing the a...
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QuickIM: Efficient, Accurate and Robust Influence Maximization Algorithm on BillionScale Networks
The Influence Maximization (IM) problem aims at finding k seed vertices ...
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Improved HorvitzThompson Estimator in Survey Sampling
The HorvitzThompson (HT) estimator is widely used in survey sampling. H...
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Subsampled Optimization: Statistical Guarantees, Mean Squared Error Approximation, and Sampling Method
For optimization on largescale data, exactly calculating its solution m...
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Gradientbased Sampling: An Adaptive Importance Sampling for Leastsquares
In modern data analysis, random sampling is an efficient and widelyused...
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Diversified Coherent Core Search on MultiLayer Graphs
Mining dense subgraphs on multilayer graphs is an interesting problem, ...
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Optimal Subsampling for Large Sample Logistic Regression
For massive data, the family of subsampling algorithms is popular to dow...
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Optimal Subsampling Approaches for Large Sample Linear Regression
A significant hurdle for analyzing large sample data is the lack of effe...
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Poisson Subsampling Algorithms for Large Sample Linear Regression in Massive Data
Large sample size brings the computation bottleneck for modern data anal...
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Rong Zhu
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