MLSP-34.5
DYNAMIC RESOURCE OPTIMIZATION FOR ADAPTIVE FEDERATED LEARNING EMPOWERED BY RECONFIGURABLE INTELLIGENT SURFACES
Claudio Battiloro, Paolo Di Lorenzo, Sergio Barbarossa, Sapienza University of Rome, Italy; Mattia Merluzzi, CEA-Leti, Université Grenoble Alpes, France
Session:
Machine Learning for Telecommunications
Track:
Machine Learning for Signal Processing
Location:
Gather Area G
Presentation Time:
Wed, 11 May, 21:00 - 21:45 China Time (UTC +8)
Wed, 11 May, 13:00 - 13:45 UTC
Wed, 11 May, 13:00 - 13:45 UTC
Session Chair:
Wee Peng Tay, Nanyang Technological University
Session MLSP-34
MLSP-34.1: LOCUNET: FAST URBAN POSITIONING USING RADIO MAPS AND DEEP LEARNING
Çağkan Yapar, Giuseppe Caire, Technische Universität Berlin, Germany; Ron Levie, Gitta Kutyniok, Ludwig-Maximilians-Universität München, Germany
MLSP-34.2: LiteHAR: LIGHTWEIGHT HUMAN ACTIVITY RECOGNITION FROM WIFI SIGNALS WITH RANDOM CONVOLUTION KERNELS
Hojjat Salehinejad, Shahrokh Valaee, University of Toronto, Canada
MLSP-34.3: CDX-Net: Cross-Domain Multi-Feature Fusion Modeling via Deep Neural Networks for Multivariate Time Series Forecasting in AIOps
Jiajia Li, Ling Dai, Bin Sheng, Shanghai Jiao Tong University, China; Feng Tan, Zikai Wang, Shanghai Artificial Intelligence Research Institute, China; Hui Shen, Shanghai Dingmao information technology Inc., China; Pengwei Hu, Merck China Innovation Hub, China
MLSP-34.4: A CLUSTERING-BASED ML SCHEME FOR CAPACITY APPROACHING SOFT LEVEL SENSING IN 3D TLC NAND
Li-Wei Liu, Yen-Ching Liao, Hsie-Chia Chang, National Yang Ming Chiao Tung University, Taiwan
MLSP-34.5: DYNAMIC RESOURCE OPTIMIZATION FOR ADAPTIVE FEDERATED LEARNING EMPOWERED BY RECONFIGURABLE INTELLIGENT SURFACES
Claudio Battiloro, Paolo Di Lorenzo, Sergio Barbarossa, Sapienza University of Rome, Italy; Mattia Merluzzi, CEA-Leti, Université Grenoble Alpes, France
MLSP-34.6: LEARNING-BASED RESOURCE ALLOCATION WITH DYNAMIC DATA RATE CONSTRAINTS
Pourya Behmandpoor, Panagiotis Patrinos, Marc Moonen, KU Leuven, Belgium