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MLSP-P2: Source Separation and Subspace Methods

Session Type: Poster
Time: Tuesday, May 28, 10:50 - 12:50
Location: Poster Area C
Session Chair: Andrzej Cichocki, RIKEN
 
  MLSP-P2.1: A RANDOMLY PERTURBED INFOMAX ALGORITHM FOR BLIND SOURCE SEPARATION
         Qi He; University of California, Irvine
         Jack Xin; University of California, Irvine
 
  MLSP-P2.2: A BOUNDED COMPONENT ANALYSIS APPROACH FOR THE SEPARATION OF CONVOLUTIVE MIXTURES OF DEPENDENT AND INDEPENDENT SOURCES
         Huseyin Inan; Koc University
         Alper Erdogan; Koc University
 
  MLSP-P2.3: FROM BASIS COMPONENTS TO COMPLEX STRUCTURAL PATTERNS
         Anh-Huy Phan; Brain Science Institute, RIKEN
         Andrzej Cichocki; Brain Science Institute, RIKEN
         Petr Tichavsky; Institute of Information Theory and Automation
         Rafal Zdunek; Wroclaw University of Technology
         Sidney Lehky; The Salk Institute
 
  MLSP-P2.4: TENSOR COMPLETION THROUGH MULTIPLE KRONECKER PRODUCT DECOMPOSITION
         Anh-Huy Phan; Brain Science Institute, RIKEN
         Andrzej Cichocki; Brain Science Institute, RIKEN
         Petr Tichavsky; Institute of Information Theory and Automation
         Gheorghe Luta; Georgetown University
         Austin J. Brockmeier; University of Florida
 
  MLSP-P2.5: PERMUTATION-FREE CONVOLUTIVE BLIND SOURCE SEPARATION VIA FULL-BAND CLUSTERING BASED ON FREQUENCY-INDEPENDENT SOURCE PRESENCE PRIORS
         Nobutaka Ito; Nippon Telegraph and Telephone Corporation
         Shoko Araki; Nippon Telegraph and Telephone Corporation
         Tomohiro Nakatani; Nippon Telegraph and Telephone Corporation
 
  MLSP-P2.6: INDEPENDENT VECTOR ANALYSIS, THE KOTZ DISTRIBUTION, AND PERFORMANCE BOUNDS
         Matthew Anderson; University of Maryland, Baltimore County
         Geng-Shen Fu; University of Maryland, Baltimore County
         Ronald Phlypo; University of Maryland, Baltimore County
         Tulay Adali; University of Maryland, Baltimore County
 
  MLSP-P2.7: ALGORITHMS FOR MARKOVIAN SOURCE SEPARATION BY ENTROPY RATE MINIMIZATION
         Geng-Shen Fu; University of Maryland, Baltimore County
         Ronald Phlypo; University of Maryland, Baltimore County
         Matthew Anderson; University of Maryland, Baltimore County
         Xi-Lin Li; Fortemedia
         Tulay Adali; University of Maryland, Baltimore County
 
  MLSP-P2.8: RANDOM PROJECTIONS: A REMEDY FOR OVERFITTING ISSUES IN TIME SERIES PREDICTION WITH ECHO STATE NETWORKS
         Lucie Daubigney; Supélec
         Matthieu Geist; Supélec
         Olivier Pietquin; Supélec-UMI 2958 (GT-CNRS)
 
  MLSP-P2.9: SUBSPACE CLUSTERING WITH DENSE REPRESENTATIONS
         Eva Dyer; Rice University
         Christoph Studer; Rice University
         Richard G. Baraniuk; Rice University
 
  MLSP-P2.10: SUBSPACE CLUSTERING VIA THRESHOLDING AND SPECTRAL CLUSTERING
         Reinhard Heckel; ETH Zurich
         Helmut Bolcskei; ETH Zurich
 
  MLSP-P2.11: THE GENERALIZED LASSO IS REDUCIBLE TO A SUBSPACE CONSTRAINED LASSO
         Hao Xu; Princeton University
         David J. Eis; Princeton University
         Peter J. Ramadge; Princeton University