SPTM-L4: Compressed Sensing and Sparsity II |
| Session Type: Lecture |
| Time: Wednesday, March 28, 14:00 - 16:00 |
| Location: Room C-2 |
| Session Chairs: Vikram Krishnamurthy, University of British Columbia and Masaaki Nagahara, Kyoto University
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SPTM-L4.1: COMPRESSIVE VIDEO RECOVERY WITH UPPER AND LOWER BOUND CONSTRAINTS
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| David Jones; University of California at Merced
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| Rachel Schlick; University of California at Merced
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| Roummel Marcia; University of California at Merced
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SPTM-L4.2: FILTERED VARIATION METHOD FOR DENOISING AND SPARSE SIGNAL PROCESSING
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| Kivanc Kose; Bilkent University
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| Volkan Cevher; École Polytechnique Fédérale de Lausanne
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| A. Enis Cetin; Bilkent University
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SPTM-L4.3: EFFICIENT RECOVERY OF BLOCK SPARSE SIGNALS VIA ZERO-POINT ATTRACTING PROJECTION
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| Jingbo Liu; Tsinghua University
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| Jian Jin; Tsinghua University
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| Yuantao Gu; Tsinghua University
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SPTM-L4.4: DESIGN OF UNIVERSAL MULTICOSET SAMPLING PATTERNS FOR COMPRESSED SENSING OF MULTIBAND SPARSE SIGNALS
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| María Elena Domínguez-Jiménez; Universidad Politécnica de Madrid
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| Nuria González-Prelcic; Universidade de Vigo
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| Gonzalo Vazquez-Vilar; Universidade de Vigo
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| Roberto López-Valcarce; Universidade de Vigo
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SPTM-L4.5: DICTIONARY LEARNING FROM SPARSELY CORRUPTED OR COMPRESSED SIGNALS
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| Christoph Studer; Rice University
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| Richard Baraniuk; Rice University
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SPTM-L4.6: RECOVERY OF BLOCK SPARSE SIGNALS USING THE FRAMEWORK OF BLOCK SPARSE BAYESIAN LEARNING
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| Zhilin Zhang; University of California at San Diego
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| Bhaskar D. Rao; University of California at San Diego
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