Rene Vidal

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Johns Hopkins University

Director of The Johns Hopkins Mathematical Institute for Data Science at The Johns Hopkins University

Doubly Stochastic Subspace Clustering

Many state-of-the-art subspace clustering methods follow a two-step proc...
11/30/2020 ∙ by Derek Lim, et al. ∙ 0 ∙ share

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A novel variational form of the Schatten-p quasi-norm

The Schatten-p quasi-norm with p∈(0,1) has recently gained considerable ...
10/26/2020 ∙ by Paris Giampouras, et al. ∙ 0 ∙ share

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A Critique of Self-Expressive Deep Subspace Clustering

Subspace clustering is an unsupervised clustering technique designed to ...
10/08/2020 ∙ by Benjamin D. Haeffele, et al. ∙ 0 ∙ share

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A Game Theoretic Analysis of Additive Adversarial Attacks and Defenses

Research in adversarial learning follows a cat and mouse game between at...
09/14/2020 ∙ by Ambar Pal, et al. ∙ 0 ∙ share

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

Finding a small set of representatives from an unlabeled dataset is a co...
06/07/2020 ∙ by Chong You, et al. ∙ 0 ∙ share

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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...
05/08/2020 ∙ by Chong You, et al. ∙ 0 ∙ share

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On Dissipative Symplectic Integration with Applications to Gradient-Based Optimization

Continuous-time dynamical systems have proved useful in providing concep...
04/15/2020 ∙ by Guilherme França, et al. ∙ 18 ∙ share

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Finding the Sparsest Vectors in a Subspace: Theory, Algorithms, and Applications

The problem of finding the sparsest vector (direction) in a low dimensio...
01/20/2020 ∙ by Qing Qu, et al. ∙ 46 ∙ share

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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...
12/30/2019 ∙ by Daniel P. Robinson, et al. ∙ 0 ∙ share

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On the Regularization Properties of Structured Dropout

Dropout and its extensions (eg. DropBlock and DropConnect) are popular h...
10/30/2019 ∙ by Ambar Pal, et al. ∙ 0 ∙ share

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Generalized Nullspace Property for Structurally Sparse Signals

We propose a new framework for studying the exact recovery of signals wi...
10/12/2019 ∙ by Mustafa D. Kaba, et al. ∙ 0 ∙ share

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The fastest ℓ_1,∞ prox in the west

Proximal operators are of particular interest in optimization problems d...
10/09/2019 ∙ by Benjamín Béjar, et al. ∙ 17 ∙ share

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Gradient Flows and Accelerated Proximal Splitting Methods

Proximal based methods are well-suited to nonsmooth optimization problem...
08/02/2019 ∙ by Guilherme França, et al. ∙ 3 ∙ share

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Neural Message Passing on Hybrid Spatio-Temporal Visual and Symbolic Graphs for Video Understanding

Many problems in video understanding require labeling multiple activitie...
05/17/2019 ∙ by Effrosyni Mavroudi, et al. ∙ 0 ∙ share

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Conformal Symplectic and Relativistic Optimization

Although momentum-based optimization methods have had a remarkable impac...
03/11/2019 ∙ by Guilherme França, et al. ∙ 0 ∙ share

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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...
12/24/2018 ∙ by Zhihui Zhu, et al. ∙ 6 ∙ share

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Nonconvex Robust Low-rank Matrix Recovery

In this paper we study the problem of recovering a low-rank matrix from ...
09/24/2018 ∙ by Xiao Li, et al. ∙ 0 ∙ share

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On Geometric Analysis of Affine Sparse Subspace Clustering

Sparse subspace clustering (SSC) is a state-of-the-art method for segmen...
08/17/2018 ∙ by Chun-Guang Li, et al. ∙ 0 ∙ share

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Relax, and Accelerate: A Continuous Perspective on ADMM

The acceleration technique first introduced by Nesterov for gradient des...
08/13/2018 ∙ by Guilherme França, et al. ∙ 0 ∙ share

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Monocular Object Orientation Estimation using Riemannian Regression and Classification Networks

We consider the task of estimating the 3D orientation of an object of kn...
07/19/2018 ∙ by Siddharth Mahendran, et al. ∙ 0 ∙ share

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Separable Dictionary Learning with Global Optimality and Applications to Diffusion MRI

Dictionary learning is a popular class of methods for modeling complex d...
07/15/2018 ∙ by Evan Schwab, et al. ∙ 0 ∙ share

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On the Implicit Bias of Dropout

Algorithmic approaches endow deep learning systems with implicit bias th...
06/26/2018 ∙ by Poorya Mianjy, et al. ∙ 0 ∙ share

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A Mixed Classification-Regression Framework for 3D Pose Estimation from 2D Images

3D pose estimation from a single 2D image is an important and challengin...
05/08/2018 ∙ by Siddharth Mahendran, et al. ∙ 0 ∙ share

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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 ...
03/26/2018 ∙ by Mengnan Zhao, et al. ∙ 0 ∙ share

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End-to-End Fine-Grained Action Segmentation and Recognition Using Conditional Random Field Models and Discriminative Sparse Coding

Fine-grained action segmentation and recognition is an important yet cha...
01/29/2018 ∙ by Effrosyni Mavroudi, et al. ∙ 0 ∙ share

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Theoretical Analysis of Sparse Subspace Clustering with Missing Entries

Sparse Subspace Clustering (SSC) is a popular unsupervised machine learn...
01/01/2018 ∙ by Manolis C. Tsakiris, et al. ∙ 0 ∙ share

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Mathematics of Deep Learning

Recently there has been a dramatic increase in the performance of recogn...
12/13/2017 ∙ by Rene Vidal, et al. ∙ 0 ∙ share

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Stretching Domain Adaptation: How far is too far?

While deep learning has led to significant advances in visual recognitio...
12/06/2017 ∙ by Yunhan Zhao, et al. ∙ 0 ∙ share

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Joint Object Category and 3D Pose Estimation from 2D Images

2D object detection is the task of finding (i) what objects are present ...
11/20/2017 ∙ by Siddharth Mahendran, et al. ∙ 0 ∙ share

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Dropout as a Low-Rank Regularizer for Matrix Factorization

Regularization for matrix factorization (MF) and approximation problems ...
10/13/2017 ∙ by Jacopo Cavazza, et al. ∙ 0 ∙ share

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An Analysis of Dropout for Matrix Factorization

Dropout is a simple yet effective algorithm for regularizing neural netw...
10/10/2017 ∙ by Jacopo Cavazza, et al. ∙ 0 ∙ share

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Structured Low-Rank Matrix Factorization: Global Optimality, Algorithms, and Applications

Recently, convex formulations of low-rank matrix factorization problems ...
08/25/2017 ∙ by Benjamin D. Haeffele, et al. ∙ 0 ∙ share

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(k,q)-Compressed Sensing for dMRI with Joint Spatial-Angular Sparsity Prior

Advanced diffusion magnetic resonance imaging (dMRI) techniques, like di...
07/21/2017 ∙ by Evan Schwab, et al. ∙ 0 ∙ share

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Hyperplane Clustering Via Dual Principal Component Pursuit

We extend the theoretical analysis of a recently proposed single subspac...
06/06/2017 ∙ by Manolis C. Tsakiris, et al. ∙ 0 ∙ share

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

Many computer vision tasks involve processing large amounts of data cont...
04/12/2017 ∙ by Chong You, et al. ∙ 0 ∙ share

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Curriculum Dropout

Dropout is a very effective way of regularizing neural networks. Stochas...
03/18/2017 ∙ by Pietro Morerio, et al. ∙ 0 ∙ share

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Information Pursuit: A Bayesian Framework for Sequential Scene Parsing

Despite enormous progress in object detection and classification, the pr...
01/09/2017 ∙ by Ehsan Jahangiri, et al. ∙ 0 ∙ share

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Joint Spatial-Angular Sparse Coding for dMRI with Separable Dictionaries

Diffusion MRI (dMRI) provides the ability to reconstruct neuronal fibers...
12/18/2016 ∙ by Evan Schwab, et al. ∙ 0 ∙ share

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Temporal Convolutional Networks for Action Segmentation and Detection

The ability to identify and temporally segment fine-grained human action...
11/16/2016 ∙ by Colin Lea, et al. ∙ 0 ∙ share

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Structured Sparse Subspace Clustering: A Joint Affinity Learning and Subspace Clustering Framework

Subspace clustering refers to the problem of segmenting data drawn from ...
10/17/2016 ∙ by Chun-Guang Li, et al. ∙ 0 ∙ share

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Temporal Convolutional Networks: A Unified Approach to Action Segmentation

The dominant paradigm for video-based action segmentation is composed of...
08/29/2016 ∙ by Colin Lea, et al. ∙ 0 ∙ share

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Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering

State-of-the-art subspace clustering methods are based on expressing eac...
05/09/2016 ∙ by Chong You, et al. ∙ 0 ∙ share

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Segmental Spatiotemporal CNNs for Fine-grained Action Segmentation

Joint segmentation and classification of fine-grained actions is importa...
02/09/2016 ∙ by Colin Lea, et al. ∙ 0 ∙ share

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Car Segmentation and Pose Estimation using 3D Object Models

Image segmentation and 3D pose estimation are two key cogs in any algori...
12/21/2015 ∙ by Siddharth Mahendran, et al. ∙ 0 ∙ share

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Filtrated Spectral Algebraic Subspace Clustering

Algebraic Subspace Clustering (ASC) is a simple and elegant method based...
10/15/2015 ∙ by Manolis C. Tsakiris, et al. ∙ 0 ∙ share

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Dual Principal Component Pursuit

We consider the problem of outlier rejection in single subspace learning...
10/15/2015 ∙ by Manolis C. Tsakiris, et al. ∙ 0 ∙ share

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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...
07/05/2015 ∙ by Chong You, et al. ∙ 0 ∙ share

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Global Optimality in Tensor Factorization, Deep Learning, and Beyond

Techniques involving factorization are found in a wide range of applicat...
06/24/2015 ∙ by Benjamin D. Haeffele, et al. ∙ 0 ∙ share

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Filtrated Algebraic Subspace Clustering

Subspace clustering is the problem of clustering data that lie close to ...
06/20/2015 ∙ by Manolis C. Tsakiris, et al. ∙ 0 ∙ share

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Dynamic Template Tracking and Recognition

In this paper we address the problem of tracking non-rigid objects whose...
04/19/2012 ∙ by Rizwan Chaudhry, et al. ∙ 0 ∙ share

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Rene Vidal

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