High dimen1_pattern recognition via sparse representation

Source: Internet
Author: User
Http://www.eecs.berkeley.edu /~ Yang/presentationpage.html

Software: http://www.eecs.berkeley.edu /~ Yang/software/softwarepage.html

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Sparse PCA via augmented Lagrangian methods
Copyright (c) UC Berkeley, 2011.

Http://www.eecs.berkeley.edu /~ Yang/software/SPCA/spca_alm.zip

Fast L-1 minimization algorithms and a performance benchmarkcopyright (c) UC Berkeley, 2010.

Http://www.eecs.berkeley.edu /~ Yang/software/l1benchmark/index.html

Presentations:
  • High dimenstmpattern recognition via sparse representation. Talk at HP Labs, 2012.
  • High dimenstmpattern recognition via sparse representation. Talk at Berkeley
    Graphics/vision seminar, and LBL seminar, 2011
  • Distributed sensing, perception, and applications on mobile devices. Seminar
    At Texas Instruments and UCB trust center, 2011.
  • Distributed sensing and perception via sparse representation. Seminar atcmu,
    JHU, llnl, UC Berkeley, UC Merced, and UT Austin, 2011.
  • DARPA geometric representation integrated DataSpace (GRID) Workshop II.
    Washington DC, 2010.
  • Distributed sensing and perception via sparse representation. Qualcomm
    Research Center Seminar, 2010.
  • Multiple-view object recognition via sparse representation. DSP
    Seminar, University of Illinois, 2009.
  • Multiple-view object recognition in band-limited distributed camera networks, icdsc,
    2009.
  • Multiple-view object recognition via sparse representation. Microsoft
    Research Asia, 2009.
  • High-dimenstmmulti-model estimation: Its algebra, statistics, and sparse representation. UT Austin,
    2009.
  • Workshop on developing shared home behavior Datasets, 2009.
  • High-dimenstmmulti-model estimation: Its algebra, statistics, and sparse representation. UC San Diego, 2009.
  • High-dimensional multi-model estimation: Its algebra, statistics, and sparse representation. Maryland, JHU, UC Merced,
    And ULOs, 2008.
  • High-dimensional multi-model estimation: Its algebra, statistics, and sparse representation. Ima Workshop on multi-manifold Data Modeling and applications, 2008
  • Q & A about recent advances in Face Recognition and how to protect your facial identity. [PDF][Website]
    • Distributed segmentation and classification of human actions using a wearable motion sensor network. cvpr Workshop
      On Human Communicative Behavior Analysis, 2008.
    • Transport Ry-based 3-D reconstruction from perspective images. cvpr tutorial, 2008.
    • Robust Face Recognition via sparse representation. NIST mbgc 2008 kickoff workshop, 2008.
    • Estimation of mixture subspace models -- its algebra, statistics, and Compressed Sensing. Upenn Department of radiology,
      2008.
    • Compressed Sensing meets machine learning. UC Berkeley trust Center Seminar, 2008.
    • Estimation of mixture subspace models -- its algebra, statistics, and Compressed Sensing. UC Berkeley
      DSP seminar, 2007.
    • Workshop on gpca. CDC, New Orleans, Dec 2007.
    • Robust statistical estimation and segmentation of multiple subspaces. cvpr Workshop on 25 years of ransac,
      2006.
    • Robust Estimation and segmentation of multiple subspaces. Berkeley Computer Vision seminar. yml,
      2006.
    • Robotalk: controlling arms, bases and androids through a single motion interface. ICAR, July, 2005.

     

    Sparse PCA via augmented Lagrangian methods

    Copyright (c) UC Berkeley, 2011.

    Http://www.eecs.berkeley.edu /~ Yang/software/SPCA/spca_alm.zip

    Fast L-1 minimization algorithms and a performance benchmark

    Copyright (c) UC Berkeley, 2010.

    Http://www.eecs.berkeley.edu /~ Yang/software/l1benchmark/index.html

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