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FR3.I: Neural Network Algorithms

Session Type: Poster
Time: Friday, 8 May, 15:15 - 17:15
Location: On-Demand
Session Chair: Sven Ewan Shepstone, Bang & Olufsen
 
   FR3.I.1: EFFICIENT DECOUPLED NEURAL ARCHITECTURE SEARCH BY STRUCTURE AND OPERATION SAMPLING
         Heung-Chang Lee; Hana Institute of Technology
         Do-Guk Kim; Hana Institute of Technology
         Bohyung Han; Seoul National University
 
   FR3.I.2: WEIGHT SHARING AND DEEP LEARNING FOR SPECTRAL DATA
         Jacob S√łgaard Larsen; Technical University of Denmark
         Line Clemmensen; Technical University of Denmark
 
   FR3.I.3: COMPLEX TRANSFORMER: A FRAMEWORK FOR MODELING COMPLEX-VALUED SEQUENCE
         Muqiao Yang; Carnegie Mellon University
         Martin Q. Ma; Carnegie Mellon University
         Dongyu Li; Carnegie Mellon University
         Yao-Hung Hubert Tsai; Carnegie Mellon University
         Ruslan Salakhutdinov; Carnegie Mellon University
 
   FR3.I.4: HIGH-DIMENSIONAL NEURAL FEATURE USING RECTIFIED LINEAR UNIT AND RANDOM MATRIX INSTANCE
         Alireza M. Javid; KTH Royal Institute of Technology
         Arun Venkitaraman; KTH Royal Institute of Technology
         Mikael Skoglund; KTH Royal Institute of Technology
         Saikat Chatterjee; KTH Royal Institute of Technology
 
   FR3.I.5: PROJECTED WEIGHT REGULARIZATION TO IMPROVE NEURAL NETWORK GENERALIZATION
         Guoqiang Zhang; university of Technology Sydney
         Niwa Kenta; NTT Media Intelligence Laboratories
         W. Bastiaan Kleijn; Victoria University of Wellington
 
   FR3.I.7: DEEP CLUSTERING FOR DOMAIN ADAPTATION
         Boyan Gao; University of Edinburgh
         Yongxin Yang; University of Edinburgh
         Henry Gouk; University of Edinburgh
         Timothy M. Hospedales; University of Edinburgh
 
   FR3.I.8: DEEP CLUSTERING WITH CONCRETE K-MEANS
         Boyan Gao; University of Edinburgh
         Yongxin Yang; University of Edinburgh
         Henry Gouk; University of Edinburgh
         Timothy M. Hospedales; University of Edinburgh
 
   FR3.I.9: POLARIZING FRONT ENDS FOR ROBUST CNNS
         Can Bakiskan; University of California, Santa Barbara
         Soorya Gopalakrishnan; University of California, Santa Barbara
         Metehan Cekic; University of California, Santa Barbara
         Upamanyu Madhow; University of California, Santa Barbara
         Ramtin Pedarsani; University of California, Santa Barbara
 
   FR3.I.10: ADAPTIVE DISTRIBUTED STOCHASTIC GRADIENT DESCENT FOR MINIMIZING DELAY IN THE PRESENCE OF STRAGGLERS
         Serge Kas Hanna; Rutgers University
         Rawad Bitar; Rutgers University
         Parimal Parag; Indian Institute of Science
         Venkat Dasari; U.S. Army Research Laboratory
         Salim El Rouayheb; Rutgers University
 
   FR3.I.11: A MODEL OF DOUBLE DESCENT FOR HIGH-DIMENSIONAL LOGISTIC REGRESSION
         Zeyu Deng; University of California, Santa Barbara
         Abla Kammoun; King Abdullah University of Science and Technology (KAUST)
         Christos Thrampoulidis; University of California, Santa Barbara
 
  FR3.I.12: LOCALIZED LINEAR REGRESSION IN NETWORKED DATA
         Alexander Jung; Aalto University
         Nguyen Tran; Aalto University