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Cycles Improve Conditional Generators
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Parameter Continuation with Secant Approximation for Deep Neural Networks
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Compressed Sensing via Partial L1 Minimization
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Improving Model Performance with Robust PCA
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Dimension Reduction and LASSO using Pointwise and Group Norms
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Anomaly Detection with Advanced Nonlinear Dimensionality Reduction
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Kernel Coherence Encoders
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Large Scale Matrix Completion and Recommender Systems
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A Detailed Accounting of Error in Neural Networks: Applications to Electromagnetics
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Analysis and Prediction of Community Structure Using Unsupervised Learning
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