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WS1-ICASSP 2024 : Deep Neural Network Model Compression, IEEE ICASSP 2024 | |||||||||||
Link: https://sites.google.com/view/icassp2024-dnnmc/home | |||||||||||
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Call For Papers | |||||||||||
https://2024.ieeeicassp.org/satellite-workshops/
https://cmsworkshops.com/ICASSP2024/workshops.php?noheader#tut1 Formatting guidelines- https://cmsworkshops.com/ICASSP2024/papers/paper_kit.php Submission link- https://cmsworkshops.com/ICASSP2024/Papers/Submission.asp?Type=WS&ID=1 Please note that the accepted papers will be IEEE Xplore indexed. Call For Papers are not limited to the following topics: Data compression (e.g., images, video, audio) with machine learning Deep Model compression Signal processing approaches for efficient learning model construction Quantization, Low-rank factorization, entropy coding, and stochastic coding Knowledge distillation Lottery Ticket Hypothesis Neural Architecture Search Fundamental performance bounds/limits of learned compression Signal processing and information theoretic models Computationally-efficient models/methods Learning efficient deep neural networks under memory and compute constraints for on-device applications On-device learning Edge analytics using efficient models for deploying industrial applications Sustainable AI Submission link: https://cmsworkshops.com/ICASSP2024/Papers/Submission.asp?Type=WS&ID=1 Workshop date: April 15, 2024 |
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