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MLSP-P18: Machine Learning Applications II

Session Type: Poster

Time: Friday, May 17, 16:00 - 18:00

Location: Poster Area G, East Landing, First Floor

Session Chair: Raviv Raich, Oregon State University

MLSP-P18.1: HYBRID DEEP NEURAL NETWORK MODEL FOR REMAINING USEFUL LIFE ESTIMATION

Ali Al-Dulaimi; Concordia University

Soheil Zabihi; Concordia University

Amir Asif; Concordia University

Arash Mohammadi; Concordia University

MLSP-P18.2: LEARNING STOCHASTIC REPRESENTATIONS OF GEOPHYSICAL DYNAMICS

Said Ouala; IMT-Atlantique

Ronan Fablet; IMT-Atlantique

Cédric Herzet; IMT Atlantique / INRIA Bretagne-Atlantique

Bertrand Chapron; IFREMER

Ananda Pascual; IMEDEA

Fabrice Collard; ODL

Lucile Gaultier; ODL

MLSP-P18.3: DEEP LEARNING FOR VERTEX RECONSTRUCTION OF NEUTRINO-NUCLEUS INTERACTION EVENTS WITH COMBINED ENERGY AND TIME DATA

Linghao Song; Duke University

Fan Chen; Duke University

Steven Young; Oak Ridge National Laboratory

Catherine Schuman; Oak Ridge National Laboratory

Gabriel Perdue; Fermi National Accelerator Laboratory

Thomas Potok; Oak Ridge National Laboratory

MLSP-P18.4: DEEP SYNTHESIZER PARAMETER ESTIMATION

Oren Barkan; Tel-Aviv Univeristy

David Tsiris; Tel-Aviv Univeristy

MLSP-P18.5: TIME SERIES PREDICTION FOR KERNEL-BASED ADAPTIVE FILTERS USING VARIABLE BANDWIDTH, ADAPTIVE LEARNING-RATE, AND DIMENSIONALITY REDUCTION

Sergio Garcia-Vega; Universidad Nacional de Colombia

Eder A. Leon-Gomez; Universidad Nacional de Colombia

German Castellanos-Dominguez; Universidad Nacional de Colombia

MLSP-P18.6: ROBUST COMMON SPATIAL PATTERNS ESTIMATION USING DYNAMIC TIME WARPING TO IMPROVE BCI SYSTEMS

Ahmed M.Azab; University of Sheffield

Lyudmila Mihaylova; University of Sheffield

Hamed Ahmadi; univversity of Essex

Mahnaz Arvaneh; University of Sheffield

MLSP-P18.7: NATIVE LANGUAGE AND STIMULI SIGNAL PREDICTION FROM EEG

Madhumitha Sakthi; The University of Texas at Austin

Ahmed Tewfik; The University of Texas at Austin

Bharath Chandrasekaran; University of Pittsburgh

MLSP-P18.8: PERFORMANCE ADVANTAGES OF DEEP NEURAL NETWORKS FOR ANGLE OF ARRIVAL ESTIMATION

Oded Bialer; General Motors

Noa Garnett; General Motors

Tom Tirer; General Motors

MLSP-P18.9: DEEP QUANTIZATION FOR MIMO CHANNEL ESTIMATION

Matan Shohat; Technion

Georgee Tsintsadze; Technion

Nir Shlezinger; Weizmann Institute

Yonina C. Eldar; Weizmann Institute

MLSP-P18.10: EFFICIENT CONVOLUTIONAL NEURAL NETWORK WEIGHT COMPRESSION FOR SPACE DATA CLASSIFICATION ON MULTI-FPGA PLATFORMS

George Pitsis; Foundation for Research and Technology-Hellas

Grigorios Tsagkatakis; Foundation for Research and Technology-Hellas

Christos Kozanitis; Foundation for Research and Technology-Hellas

Ioannis Kalomoiris; Foundation for Research and Technology-Hellas

Aggelos Ioannou; Foundation for Research and Technology-Hellas

Apostolos Dollas; Foundation for Research and Technology-Hellas

Manolis Katevenis; Foundation for Research and Technology-Hellas

Panagiotis Tsakalides; Foundation for Research and Technology-Hellas

MLSP-P18.11: CRIME EVENT EMBEDDING WITH UNSUPERVISED FEATURE SELECTION

Shixiang Zhu; Georgia Institute of Technology

Yao Xie; Georgia Institute of Technology