NEWS MERL Researchers give a Tutorial Talk on Quantum Machine Learning for Sensing and Communications at IEEE VCC
Date released: November 21, 2023
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NEWS MERL Researchers give a Tutorial Talk on Quantum Machine Learning for Sensing and Communications at IEEE VCC Date:
November 28, 2023 - November 30, 2023
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Where:
Virtual
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Description:
On November 28, 2023, MERL researchers Toshiaki Koike-Akino and Pu (Perry) Wang will give a 3-hour tutorial presentation at the first IEEE Virtual Conference on Communications (VCC). The talk, titled "Post-Deep Learning Era: Emerging Quantum Machine Learning for Sensing and Communications," addresses recent trends, challenges, and advances in sensing and communications. P. Wang presents use cases, industry trends, signal processing, and deep learning for Wi-Fi integrated sensing and communications (ISAC), while T. Koike-Akino discusses the future of deep learning, giving a comprehensive overview of artificial intelligence (AI) technologies, natural computing, emerging quantum AI, and their diverse applications. The tutorial is conducted virtually.
IEEE VCC is a new fully virtual conference launched from the IEEE Communications Society, gathering researchers from academia and industry who are unable to travel but wish to present their recent scientific results and engage in conducive interactive discussions with fellow researchers working in their fields. It is designed to resolve potential hardship such as pandemic restrictions, visa issues, travel problems, or financial difficulties. -
External Link:
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MERL Contacts:
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Research Areas:
Artificial Intelligence, Communications, Computational Sensing, Machine Learning, Signal Processing
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BibTeX TR2023-097 PDF- @inproceedings{Ahmed2023aug2,
- author = {Ahmed, Md Rubel and Koike-Akino, Toshiaki and Parsons, Kieran and Wang, Ye},
- title = {AutoHLS: Learning to Accelerate Design Space Exploration for HLS Designs},
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BibTeX TR2022-110 PDF Video Presentation- @inproceedings{Koike-Akino2022aug,
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- year = 2022,
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- doi = {10.1109/ICC45855.2022.9839011},
- issn = {1938-1883},
- isbn = {978-1-5386-8347-7},
- url = {https://www.merl.com/publications/TR2022-044}
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