
Sequential Quadratic Optimization for Nonlinear Equality Constrained Stochastic Optimization
Sequential quadratic optimization algorithms are proposed for solving sm...
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SelfRepresentation Based Unsupervised Exemplar Selection in a Union of Subspaces
Finding a small set of representatives from an unlabeled dataset is a co...
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Is an Affine Constraint Needed for Affine Subspace Clustering?
Subspace clustering methods based on expressing each data point as a lin...
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Basis Pursuit and Orthogonal Matching Pursuit for Subspacepreserving Recovery: Theoretical Analysis
Given an overcomplete dictionary A and a signal b = Ac^* for some sparse...
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Generalized Nullspace Property for Structurally Sparse Signals
We propose a new framework for studying the exact recovery of signals wi...
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Gradient Flows and Accelerated Proximal Splitting Methods
Proximal based methods are wellsuited to nonsmooth optimization problem...
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Conformal Symplectic and Relativistic Optimization
Although momentumbased optimization methods have had a remarkable impac...
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Dual Principal Component Pursuit: Probability Analysis and Efficient Algorithms
Recent methods for learning a linear subspace from data corrupted by out...
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Relax, and Accelerate: A Continuous Perspective on ADMM
The acceleration technique first introduced by Nesterov for gradient des...
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Sparse Recovery over Graph Incidence Matrices: Polynomial Time Guarantees and Location Dependent Performance
Classical results in sparse recovery guarantee the exact reconstruction ...
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Complexity Analysis of a Trust Funnel Algorithm for Equality Constrained Optimization
A method is proposed for solving equality constrained nonlinear optimiza...
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Provable SelfRepresentation Based Outlier Detection in a Union of Subspaces
Many computer vision tasks involve processing large amounts of data cont...
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Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering
Stateoftheart subspace clustering methods are based on expressing eac...
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TradingOff Cost of Deployment Versus Accuracy in Learning Predictive Models
Predictive models are finding an increasing number of applications in ma...
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Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit
Subspace clustering methods based on ℓ_1, ℓ_2 or nuclear norm regulariza...
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Daniel P. Robinson
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