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184 lines
6.9 KiB
BibTeX
184 lines
6.9 KiB
BibTeX
@misc{Thefutur92:online,
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author = {ARM.com},
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title = {The future is being built on Arm: Market diversification continues to drive strong royalty and licensing growth as ecosystem reaches quarter of a trillion chips milestone – Arm®},
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howpublished = {\url{https://www.arm.com/company/news/2023/02/arm-announces-q3-fy22-results}},
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month = {},
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year = {},
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note = {(Accessed on 09/16/2023)}
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}
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@article{han2015deep,
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title={Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding},
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author={Han, Song and Mao, Huizi and Dally, William J},
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journal={arXiv preprint arXiv:1510.00149},
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year={2015}
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}
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@misc{han2016deep,
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title={Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding},
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author={Song Han and Huizi Mao and William J. Dally},
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year={2016},
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eprint={1510.00149},
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archivePrefix={arXiv},
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primaryClass={cs.CV}
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}
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@article{lecun1989optimal,
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title={Optimal brain damage},
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author={LeCun, Yann and Denker, John and Solla, Sara},
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journal={Advances in neural information processing systems},
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volume={2},
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year={1989}
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}
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@book{barroso2019datacenter,
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title={The datacenter as a computer: Designing warehouse-scale machines},
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author={Barroso, Luiz Andr{\'e} and H{\"o}lzle, Urs and Ranganathan, Parthasarathy},
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year={2019},
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publisher={Springer Nature}
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}
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@article{howard2017mobilenets,
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title={Mobilenets: Efficient convolutional neural networks for mobile vision applications},
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author={Howard, Andrew G and Zhu, Menglong and Chen, Bo and Kalenichenko, Dmitry and Wang, Weijun and Weyand, Tobias and Andreetto, Marco and Adam, Hartwig},
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journal={arXiv preprint arXiv:1704.04861},
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year={2017}
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}
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@inproceedings{he2016deep,
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title={Deep residual learning for image recognition},
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author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
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booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
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pages={770--778},
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year={2016}
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}
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@inproceedings{jouppi2017datacenter,
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title={In-datacenter performance analysis of a tensor processing unit},
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author={Jouppi, Norman P and Young, Cliff and Patil, Nishant and Patterson, David and Agrawal, Gaurav and Bajwa, Raminder and Bates, Sarah and Bhatia, Suresh and Boden, Nan and Borchers, Al and others},
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booktitle={Proceedings of the 44th annual international symposium on computer architecture},
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pages={1--12},
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year={2017}
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}
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@article{iandola2016squeezenet,
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title={SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and< 0.5 MB model size},
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author={Iandola, Forrest N and Han, Song and Moskewicz, Matthew W and Ashraf, Khalid and Dally, William J and Keutzer, Kurt},
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journal={arXiv preprint arXiv:1602.07360},
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year={2016}
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}
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@article{li2019edge,
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title={Edge AI: On-demand accelerating deep neural network inference via edge computing},
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author={Li, En and Zeng, Liekang and Zhou, Zhi and Chen, Xu},
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journal={IEEE Transactions on Wireless Communications},
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volume={19},
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number={1},
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pages={447--457},
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year={2019},
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publisher={IEEE}
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}
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@book{rosenblatt1957perceptron,
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title={The perceptron, a perceiving and recognizing automaton Project Para},
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author={Rosenblatt, Frank},
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year={1957},
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publisher={Cornell Aeronautical Laboratory}
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}
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@article{rumelhart1986learning,
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title={Learning representations by back-propagating errors},
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author={Rumelhart, David E and Hinton, Geoffrey E and Williams, Ronald J},
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journal={nature},
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volume={323},
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number={6088},
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pages={533--536},
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year={1986},
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publisher={Nature Publishing Group UK London}
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}
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@book{warden2019tinyml,
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title={Tinyml: Machine learning with tensorflow lite on arduino and ultra-low-power microcontrollers},
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author={Warden, Pete and Situnayake, Daniel},
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year={2019},
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publisher={O'Reilly Media}
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}
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@inproceedings{jouppi2017datacenter,
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title={In-datacenter performance analysis of a tensor processing unit},
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author={Jouppi, Norman P and Young, Cliff and Patil, Nishant and Patterson, David and Agrawal, Gaurav and Bajwa, Raminder and Bates, Sarah and Bhatia, Suresh and Boden, Nan and Borchers, Al and others},
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booktitle={Proceedings of the 44th annual international symposium on computer architecture},
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pages={1--12},
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year={2017}
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}
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@article{krizhevsky2012imagenet,
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title={Imagenet classification with deep convolutional neural networks},
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author={Krizhevsky, Alex and Sutskever, Ilya and Hinton, Geoffrey E},
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journal={Advances in neural information processing systems},
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volume={25},
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year={2012}
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}
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@inproceedings{chen2018tvm,
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title={$\{$TVM$\}$: An automated $\{$End-to-End$\}$ optimizing compiler for deep learning},
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author={Chen, Tianqi and Moreau, Thierry and Jiang, Ziheng and Zheng, Lianmin and Yan, Eddie and Shen, Haichen and Cowan, Meghan and Wang, Leyuan and Hu, Yuwei and Ceze, Luis and others},
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booktitle={13th USENIX Symposium on Operating Systems Design and Implementation (OSDI 18)},
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pages={578--594},
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year={2018}
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}
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@article{paszke2019pytorch,
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title={Pytorch: An imperative style, high-performance deep learning library},
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author={Paszke, Adam and Gross, Sam and Massa, Francisco and Lerer, Adam and Bradbury, James and Chanan, Gregory and Killeen, Trevor and Lin, Zeming and Gimelshein, Natalia and Antiga, Luca and others},
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journal={Advances in neural information processing systems},
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volume={32},
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year={2019}
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}
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@inproceedings{abadi2016tensorflow,
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title={$\{$TensorFlow$\}$: a system for $\{$Large-Scale$\}$ machine learning},
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author={Abadi, Mart{\'\i}n and Barham, Paul and Chen, Jianmin and Chen, Zhifeng and Davis, Andy and Dean, Jeffrey and Devin, Matthieu and Ghemawat, Sanjay and Irving, Geoffrey and Isard, Michael and others},
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booktitle={12th USENIX symposium on operating systems design and implementation (OSDI 16)},
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pages={265--283},
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year={2016}
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}
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@misc{chollet2015,
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author = {François Chollet },
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title = {keras},
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year = {2015},
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publisher = {GitHub},
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journal = {GitHub repository},
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howpublished = {\url{https://github.com/fchollet/keras}},
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commit = {5bcac37}
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}
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@article{vaswani2017attention,
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title={Attention is all you need},
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author={Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and Uszkoreit, Jakob and Jones, Llion and Gomez, Aidan N and Kaiser, {\L}ukasz and Polosukhin, Illia},
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journal={Advances in neural information processing systems},
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volume={30},
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year={2017}
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}
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@article{goodfellow2020generative,
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title={Generative adversarial networks},
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author={Goodfellow, Ian and Pouget-Abadie, Jean and Mirza, Mehdi and Xu, Bing and Warde-Farley, David and Ozair, Sherjil and Courville, Aaron and Bengio, Yoshua},
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journal={Communications of the ACM},
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volume={63},
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number={11},
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pages={139--144},
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year={2020},
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publisher={ACM New York, NY, USA}
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}
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@article{bank2023autoencoders,
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title={Autoencoders},
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author={Bank, Dor and Koenigstein, Noam and Giryes, Raja},
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journal={Machine Learning for Data Science Handbook: Data Mining and Knowledge Discovery Handbook},
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pages={353--374},
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year={2023},
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publisher={Springer}
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} |