TA6b2.4

Deep Learning-Based Pilotless Spatial Multiplexing

Dani Korpi, Mikko Honkala, Janne M.J. Huttunen, Nokia Bell Labs, Finland
Session:
TA6b2: Deep Learning Poster
Track:
Adaptive Systems, Machine Learning, Data Analytics
Location:
Kiln
Presentation Time:
Tue, 31 Oct, 10:15 - 11:55 PT (UTC -8)
Session Chair:
Matthew Ziemann, US Army DEVCOM Army Research Lab
Presentation
Discussion
Resources
No resources available.
Session TA6b2
TA6b2.1: Empowering Artificial Neural Networks by adding Biological Dendrites
Spyridon Chavlis, Panayiota Poirazi, Foundation for Research and Technology-Hellas (FORTH), Greece
TA6b2.2: Radiation Anomaly Detection Using an Adversarial Autoencoder
Charles Sayre, Eric Larson, Gabs DiLiegro, Joseph Camp, Southern Methodist University, United States; Bruce Gnade, University of Texas at Dallas, United States
TA6b2.3: A Generative Neighborhood-Based Deep Autoencoder with an Extended Loss Function for Robust Imbalanced Classification
Eirini Troullinou, Grigorios Tsagkatakis, University of Crete, Greece; Attila Losonczy, Columbia University, United States; Panayiota Poirazi, IMBB-FORTH, Greece; Panagiotis Tsakalides, University of Crete, Greece
TA6b2.4: Deep Learning-Based Pilotless Spatial Multiplexing
Dani Korpi, Mikko Honkala, Janne M.J. Huttunen, Nokia Bell Labs, Finland
TA6b2.5: Adaptive LPD Radar Waveform Design with Generative Adversarial Neural Networks
Matthew Ziemann, DEVCOM Army Research Laboratory, United States; Christopher Metzler, University of Maryland, United States
TA6b2.6: DeepGRAND: Deep Graph Neural Diffusion
Khang Nguyen, Hieu Nong, Khuong Nguyen, FSOFT AI Center, Viet Nam; Tan Nguyen, University of California, Los Angeles, United States; Vinh Nguyen, FSOFT AI Center, Viet Nam
TA6b2.7: A Novel Methodology for Accurate 12-Lead ECG Reconstruction
Dorsa EPMoghaddam, Anton Banta, Rice University, United States; Allison Post, Mehdi Razavi, Texas Heart Institute, United States; Behnaam Aazhang, Rice University, United States
TA6b2.8: Optimization of Communication-Efficient Online Federated Learning for Time-series Data
Dohyeok Kwon, Songnam Hong, Hanyang University, Republic of Korea
TA6b2.9: Solving Large-scale Spatial Problems with Convolutional Neural Networks
Damian Owerko, Charilaos Kanatsoulis, Alejandro Ribeiro, University of Pennsylvania, United States
TA6b2.10: Trust, but Verify: Robust Image Segmentation using Deep Learning
Fahim Ahmed Zaman, Xiaodong Wu, Weiyu Xu, Milan Sonka, Raghuraman Mudumbai, University of Iowa, United States
TA6b2.11: Complex-Valued Deep-Learning Model for 3D SAR Modeling and Image Generation
Nithin Sugavanam, Emre Ertin, The Ohio State University, United States
Contacts