CCNC 2021: WORK-IN-PROGRESS (I) - AI/ML

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IEEE Consumer Communications & Networking Conference 9-12 January 2021 // Virtual Conference WORK-IN-PROGRESS (I) - AI/ML.
 

A Reinforcement Learning Approach to ARQ Feedback-based Multiple Access for Cognitive Radio Networks Sara Attalla (AUC & Alexandria, Egypt); Karim G. Seddik (American University in Cairo, Egypt); Amr El-Sherif (Nile University, Egypt); Tamer ElBatt (The American University in Cairo (AUC) & Faculty of Engineering, Cairo University, Egypt)

Applying Q-learning approach to CSMA Scheme to dynamically tune the contention probability Floriano De Rango, Nicola Cordeschi and Francisco Ritacco (University of Calabria, Italy)

Deep-Reinforcement Learning for Fair Distributed Dynamic Spectrum Access in Wireless Networks Siavash Barqi Janiar and Vahid Pourahmadi (Amirkabir University of Technology, Iran)

Complex Autoencoder Approach to Constant Envelope Waveform Coding Paul E Gorday, Nurgun Erdol and Hanqi Zhuang (Florida Atlantic University, USA)

Label Leakage from Gradients in Distributed Machine Learning Aidmar Wainakh and Till M¸flig (TU Darmstadt, Germany); Tim Grube (Technische Universitaet Darmstadt, Germany); Max M¸hlh‰user (TU-Darmstadt, Germany)

Machine-Learning directed Article Detection on the Web using DOM and text-based features Shobhit Mathur, Pritam Nikam and Harshita Patidar (Samsung R&D Bangalore, India); Rohan Gaikwad (Veermata Jijabai Technological Institute Mumbai, India); Preeti Nayak (Samsung R&D Institute India - Bangalore, India)

IEEE Consumer Communications & Networking Conference 9-12 January 2021 // Virtual Conference WORK-IN-PROGRESS (I) - AI/ML

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