
Randomized Algorithms for Scientific Computing (RASC)
Randomized algorithms have propelled advances in artificial intelligence...
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Variance Reduction via PrimalDual Accelerated Dual Averaging for Nonsmooth Convex FiniteSums
We study structured nonsmooth convex finitesum optimization that appear...
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Manifold Learning and Nonlinear Homogenization
We describe an efficient domain decompositionbased framework for nonlin...
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Random Coordinate Underdamped Langevin Monte Carlo
The Underdamped Langevin Monte Carlo (ULMC) is a popular Markov chain Mo...
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Random Coordinate Langevin Monte Carlo
Langevin Monte Carlo (LMC) is a popular Markov chain Monte Carlo samplin...
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Adversarial Classification via Distributional Robustness with Wasserstein Ambiguity
We study a model for adversarial classification based on distributionall...
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Interleaved Composite Quantization for HighDimensional Similarity Search
Similarity search retrieves the nearest neighbors of a query vector from...
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A Distributed QuasiNewton Algorithm for Primal and Dual Regularized Empirical Risk Minimization
We propose a communication and computationefficient distributed optimi...
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Schwarz iteration method for elliptic equation with rough media based on random sampling
We propose a computationally efficient Schwarz method for elliptic equat...
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A Distributed QuasiNewton Algorithm for Empirical Risk Minimization with Nonsmooth Regularization
In this paper, we propose a communication and computation efficient di...
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Training Set Debugging Using Trusted Items
Training set bugs are flaws in the data that adversely affect machine le...
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Using Neural Networks to Detect Line Outages from PMU Data
We propose an approach based on neural networks and the AC power flow eq...
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Online Algorithms for FactorizationBased Structure from Motion
We present a family of online algorithms for realtime factorizationbas...
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On GROUSE and Incremental SVD
GROUSE (Grassmannian RankOne Update Subspace Estimation) is an incremen...
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Robust Dequantized Compressive Sensing
We consider the reconstruction problem in compressed sensing in which th...
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Approximate Stochastic Subgradient Estimation Training for Support Vector Machines
Subgradient algorithms for training support vector machines have been qu...
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Convex Approaches to Model Wavelet Sparsity Patterns
Statistical dependencies among wavelet coefficients are commonly represe...
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Stephen J. Wright
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