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p-Meta: Towards On-device Deep Model Adaptation


Jun 25, 2022
Zhongnan Qu, Zimu Zhou, Yongxin Tong, Lothar Thiele

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* Published in SIGKDD 2022 

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Hyper Attention Recurrent Neural Network: Tackling Temporal Covariate Shift in Time Series Analysis


Feb 22, 2022
Wenying Duan, Xiaoxi He, Lu Zhou, Zimu Zhou, Lothar Thiele, Hong Rao

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* 6 pages, 4 figures 

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Memory-Aware Partitioning of Machine Learning Applications for Optimal Energy Use in Batteryless Systems


Aug 05, 2021
Andres Gomez, Andreas Tretter, Pascal Alexander Hager, Praveenth Sanmugarajah, Luca Benini, Lothar Thiele

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Using system context information to complement weakly labeled data


Jul 19, 2021
Matthias Meyer, Michaela Wenner, Clément Hibert, Fabian Walter, Lothar Thiele

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* Also appears in "Proceedings of the First Workshop on Weakly Supervised Learning (WeaSuL)" arXiv:2107.03690 

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Measuring what Really Matters: Optimizing Neural Networks for TinyML


Apr 21, 2021
Lennart Heim, Andreas Biri, Zhongnan Qu, Lothar Thiele

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Deep Partial Updating


Jul 06, 2020
Zhongnan Qu, Cong Liu, Junfeng Guo, Lothar Thiele

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Adaptive Loss-aware Quantization for Multi-bit Networks


Dec 18, 2019
Zhongnan Qu, Zimu Zhou, Yun Cheng, Lothar Thiele

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Disentangling Redundancy for Multi-Task Pruning


May 23, 2019
Xiaoxi He, Dawei Gao, Zimu Zhou, Yongxin Tong, Lothar Thiele

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Event-triggered Natural Hazard Monitoring with Convolutional Neural Networks on the Edge


Oct 22, 2018
Matthias Meyer, Timo Farei-Campagna, Akos Pasztor, Reto Da Forno, Tonio Gsell, Samuel Weber, Jan Beutel, Lothar Thiele

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Multi-Task Zipping via Layer-wise Neuron Sharing


May 24, 2018
Xiaoxi He, Zimu Zhou, Lothar Thiele

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