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Qi Wang
125 publications
Rene Vidal
78 publications
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35 publications
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Suchi Saria
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Jeremias Sulam
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Xinyue Zhang
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∙ 04/28/2023

A Stochastic-Gradient-based Interior-Point Algorithm for Solving Smooth Bound-Constrained Optimization Problems

A stochastic-gradient-based interior-point algorithm for minimizing a co...

0 Frank E. Curtis, et al. ∙

∙ 10/06/2021

Boosting RANSAC via Dual Principal Component Pursuit

In this paper, we revisit the problem of local optimization in RANSAC. O...

9 Yunchen Yang, et al. ∙

∙ 06/24/2021

A Stochastic Sequential Quadratic Optimization Algorithm for Nonlinear Equality Constrained Optimization with Rank-Deficient Jacobians

A sequential quadratic optimization algorithm is proposed for solving sm...

0 Albert S. Berahas, et al. ∙

∙ 07/20/2020

Sequential Quadratic Optimization for Nonlinear Equality Constrained Stochastic Optimization

Sequential quadratic optimization algorithms are proposed for solving sm...

0 Albert Berahas, et al. ∙

∙ 06/07/2020

Self-Representation Based Unsupervised Exemplar Selection in a Union of Subspaces

Finding a small set of representatives from an unlabeled dataset is a co...

0 Chong You, et al. ∙

∙ 05/08/2020

Is an Affine Constraint Needed for Affine Subspace Clustering?

Subspace clustering methods based on expressing each data point as a lin...

0 Chong You, et al. ∙

∙ 12/30/2019

Basis Pursuit and Orthogonal Matching Pursuit for Subspace-preserving Recovery: Theoretical Analysis

Given an overcomplete dictionary A and a signal b = Ac^* for some sparse...

0 Daniel P. Robinson, et al. ∙

∙ 10/12/2019

Generalized Nullspace Property for Structurally Sparse Signals

We propose a new framework for studying the exact recovery of signals wi...

0 Mustafa D. Kaba, et al. ∙

∙ 08/02/2019

Gradient Flows and Accelerated Proximal Splitting Methods

Proximal based methods are well-suited to nonsmooth optimization problem...

3 Guilherme França, et al. ∙

∙ 03/11/2019

Conformal Symplectic and Relativistic Optimization

Although momentum-based optimization methods have had a remarkable impac...

0 Guilherme França, et al. ∙

∙ 12/24/2018

Dual Principal Component Pursuit: Probability Analysis and Efficient Algorithms

Recent methods for learning a linear subspace from data corrupted by out...

7 Zhihui Zhu, et al. ∙

∙ 08/13/2018

Relax, and Accelerate: A Continuous Perspective on ADMM

The acceleration technique first introduced by Nesterov for gradient des...

0 Guilherme França, et al. ∙

∙ 03/26/2018

Sparse Recovery over Graph Incidence Matrices: Polynomial Time Guarantees and Location Dependent Performance

Classical results in sparse recovery guarantee the exact reconstruction ...

0 Mengnan Zhao, et al. ∙

∙ 07/02/2017

Complexity Analysis of a Trust Funnel Algorithm for Equality Constrained Optimization

A method is proposed for solving equality constrained nonlinear optimiza...

0 Frank E. Curtis, et al. ∙

∙ 04/12/2017

Provable Self-Representation Based Outlier Detection in a Union of Subspaces

Many computer vision tasks involve processing large amounts of data cont...

0 Chong You, et al. ∙

∙ 05/09/2016

Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering

State-of-the-art subspace clustering methods are based on expressing eac...

0 Chong You, et al. ∙

∙ 04/20/2016

Trading-Off Cost of Deployment Versus Accuracy in Learning Predictive Models

Predictive models are finding an increasing number of applications in ma...

0 Daniel P. Robinson, et al. ∙

∙ 07/05/2015

Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit

Subspace clustering methods based on ℓ_1, ℓ_2 or nuclear norm regulariza...

0 Chong You, et al. ∙

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