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TU1.I: Dictionary Learning, Representation Learning and Matrix Completion

Session Type: Poster
Time: Tuesday, 5 May, 11:30 - 13:30
Location: On-Demand
Session Chair: Dmitriy Shutin, German Aerospace Center (DLR)
 
   TU1.I.1: LOW MUTUAL AND AVERAGE COHERENCE DICTIONARY LEARNING USING CONVEX APPROXIMATION
         Javad Parsa; Sharif University of Technology
         Mostafa Sadeghi; Inria Grenoble Rhône-Alpes
         Massoud Babaie-Zadeh; Sharif University of Technology
         Christian Jutten; GIPSA-Lab
 
   TU1.I.2: ROBUST ONLINE MATRIX COMPLETION WITH GAUSSIAN MIXTURE MODEL
         Chunsheng Liu; National University of Defense Technology
         Chunlei Chen; Weifang University
         Hong Shan; National University of Defense Technology
         Bin Wang; National University of Defense Technology
 
   TU1.I.3: DEEP NEURAL NETWORK BASED MATRIX COMPLETION FOR INTERNET OF THINGS NETWORK LOCALIZATION
         Sunwoo Kim; Seoul National University
         Luong Trung Nguyen; Seoul National University
         Byonghyo Shim; Seoul National University
 
   TU1.I.4: BRINGING IN THE OUTLIERS: A SPARSE SUBSPACE CLUSTERING APPROACH TO LEARN A DICTIONARY OF MOUSE ULTRASONIC VOCALIZATIONS
         Jiaxi Wang; University of Southern California
         Karel Mundnich; University of Southern California
         Allison Knoll; University of Southern California
         Pat Levitt; University of Southern California
         Shrikanth Narayanan; University of Southern California
 
   TU1.I.5: ONE-BIT COMPRESSED SENSING USING GENERATIVE MODELS
         Geethu Joseph; Syracuse University
         Swatantra Kafle; Syracuse University
         Pramod Varshney; Syracuse University
 
   TU1.I.6: HYBRID DEEP-SEMANTIC MATRIX FACTORIZATION FOR TAG-AWARE PERSONALIZED RECOMMENDATION
         Zhenghua Xu; Hebei University of Technology
         Di Yuan; Hebei University of Technology
         Thomas Lukasiewicz; University of Oxford
         Cheng Chen; China Academy of Electronics and Information Technology
         Yishu Miao; University of Oxford
         Guizhi Xu; Hebei University of Technology
 
   TU1.I.7: SUPERVISED ENCODING FOR DISCRETE REPRESENTATION LEARNING
         Cat Le; Duke University
         Yi Zhou; University of Utah
         Jie Ding; University of Minnesota
         Vahid Tarokh; Duke University
 
   TU1.I.8: LEARNING DATA REPRESENTATION AND EMOTION ASSESSMENT FROM PHYSIOLOGICAL DATA
         Miguel Joaquim; Universidade de Lisboa
         Rita Maçorano; Universidade de Lisboa
         Francisca Canais; Universidade de Lisboa
         Rafael Ramos; Universidade de Lisboa
         Ana Fred; Instituto Superior Técnico, Universidade de Lisboa
         Marco Torrado; Universidade de Lisboa
         Hugo Ferreira; Universidade de Lisboa
 
   TU1.I.9: FEATURE SELECTION UNDER ORTHOGONAL REGRESSION WITH REDUNDANCY MINIMIZING
         Xueyuan Xu; Beijing Normal University
         Xia Wu; Beijing Normal University
 
   TU1.I.10: THE PICASSO ALGORITHM FOR BAYESIAN LOCALIZATION VIA PAIRED COMPARISONS IN A UNION OF SUBSPACES MODEL
         Gregory Canal; Georgia Institute of Technology
         Marissa Connor; Georgia Institute of Technology
         Jihui Jin; Georgia Institute of Technology
         Namrata Nadagouda; Georgia Institute of Technology
         Matthew O'Shaughnessy; Georgia Institute of Technology
         Christopher Rozell; Georgia Institute of Technology
         Mark Davenport; Georgia Institute of Technology
 
   TU1.I.11: LEARNING SEMI-SUPERVISED ANONYMIZED REPRESENTATIONS BY MUTUAL INFORMATION
         Clement Feutry; CentraleSupelec-CNRS-Universite Paris Sud
         Pablo Piantanida; CentraleSupelec-CNRS-Universite Paris Sud
         Pierre Duhamel; CNRS-CentraleSupelec-Universite Paris Sud
 
   TU1.I.12: LEARNING LOCAL STRUCTURE OF REPRESENTATIVE POINTS FOR POINT CLOUD CLASSIFICATION AND SEMANTIC SEGMENTATION
         Xincheng Li; Tianjin University
         Yanwei Pang; Tianjin University
         Yuefeng Wu; Tianjin University
         Yazhao Li; Tianjin University