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Perceptual Generative Autoencoders
Modern generative models are usually designed to match target distributi...
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Removing the Feature Correlation Effect of Multiplicative Noise
Multiplicative noise, including dropout, is widely used to regularize de...
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Circular-shift Linear Network Codes with Arbitrary Odd Block Lengths
Circular-shift linear network coding (LNC) is a special type of vector L...
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A Block-wise, Asynchronous and Distributed ADMM Algorithm for General Form Consensus Optimization
Many machine learning models, including those with non-smooth regularize...
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Asynchronous Stochastic Proximal Methods for Nonconvex Nonsmooth Optimization
We study stochastic algorithms for solving non-convex optimization probl...
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Batch Auction Design For Cloud Container Services
Cloud containers represent a new, light-weight alternative to virtual ma...
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Online Job Scheduling in Distributed Machine Learning Clusters
Nowadays large-scale distributed machine learning systems have been depl...
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Device-to-Device Load Balancing for Cellular Networks
Small-cell architecture is widely adopted by cellular network operators ...
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Normalized Direction-preserving Adam
Optimization algorithms for training deep models not only affects the co...
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Expectile Matrix Factorization for Skewed Data Analysis
Matrix factorization is a popular approach to solving matrix estimation ...
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