Rene Vidal

Rene Vidal

Baltimore, Maryland, United States
3K followers 500+ connections

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About

Rene Vidal received his B.S. degree in Electrical Engineering (highest honors) from the…

Contributions

Activity

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Experience

  • University of Pennsylvania Graphic

    University of Pennsylvania

    Philadelphia, Pennsylvania, United States

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    Baltimore, Maryland Area

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    Baltimore, Maryland Area

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    Baltimore, Maryland Area

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    Baltimore, Maryland Area

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    Paris, France

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    Santiago Chile

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    Baltimore, Maryland Area

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Education

  • University of California, Berkeley Graphic

    University of California, Berkeley

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    Activities and Societies: International House

    Developed vision-based algorithms for landing a helicopter on a moving platform.

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    Activities and Societies: Salsa dancing

    Studied multibody multiview geometry and developed motion segmentation algorithms

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    Studied electrical engineering.

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    Studied electrical engineering

Publications

  • Global Optimality in Tensor Factorization, Deep Learning, and Beyond

    arxiv

    While deep learning approaches have revolutionized machine learning, computer vision, speech and language processing, the theoretical reasons for its success remain elusive. This work studies conditions for global optimality in deep learning. In particular, it is shown that if the output of the network and the network regularizer are positively homogeneous functions of the network weights, all local minima that satisfy a simple condition are global minima.

    Other authors
    • Ben Haeffele
    See publication

Patents

  • System and method for aligning video sequences

    Issued US US 9025908 B2

    Methods and Systems for aligning multiple video sequences of a similar scene. It is determined which video sequences should be aligned with each other using linear dynamic system (LDS) modeling. The video sequences are then spatially aligned with each other.

    See patent

Projects

  • Sparse Subspace Clustering

    - Present

    Subspace clustering is an important problem with numerous applications in image processing and computer vision. Given a set of points drawn from a union of linear or affine subspaces, the task is to find segmentation of the data. In most applications the data are embedded in high-dimensional spaces, while the underlying subspaces are low-dimensional. In this project, we propose a new approach to subspace clustering based on sparse representation. We exploit the fact that each data point in a…

    Subspace clustering is an important problem with numerous applications in image processing and computer vision. Given a set of points drawn from a union of linear or affine subspaces, the task is to find segmentation of the data. In most applications the data are embedded in high-dimensional spaces, while the underlying subspaces are low-dimensional. In this project, we propose a new approach to subspace clustering based on sparse representation. We exploit the fact that each data point in a union of subspaces can always be written as a linear or affine combination of all other points. By searching for the sparsest combination, we automatically obtain a representation from points lying in the same subspace. This allows us to build a similarity matrix, from which the segmentation of the data can be easily obtained using spectral clustering. While in principle finding the sparsest representation is an NP hard problem, we show that under mild assumptions on the distribution of the data across subspaces, the sparsest representation can be found efficiently by solving a convex optimization problem.

    Other creators
    • Ehsan Elhamifar
    See project

  • GPCA

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    GPCA is an algebraic algorithm for clustering data drawn from a union of subspaces.

    Other creators
    • Yi Ma
    See project

Honors & Awards

  • IAPR Fellow

    IAPR

    For contributions to computer vision and pattern recognition.

  • IEEE Fellow

    IEEE

  • Best Paper Award ICCV Workshop on 3D Reconstruction and Recognition

    IEEE

  • Best Paper Award, ICCV Workshop on 3D Representation and Recognition

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  • Best Paper Award, Conference on Decision and Control

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  • J.K. Aggarwal Award Prize

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  • Best Paper Award in Medical Robotics and Computer Assisted Interventions

    MICCAI

    Best Paper Award in Medical Robotics and Computer Assisted Interventions for paper entitled “Surgical Gesture Classification from Video Data”, MICCAI 2012

Languages

  • English

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  • Spanish

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  • French

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Organizations

  • IEEE

    Associate Editor of TPAMI

    - Present

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