Zobrazeno 1 - 10
of 69
pro vyhledávání: '"Quoc V, Le"'
Autor:
Sheng Li, Garrett Andersen, Tao Chen, Liqun Cheng, Julian Grady, Da Huang, Quoc V. Le, Andrew Li, Xin Li, Yang Li, Chen Liang, Yifeng Lu, Yun Ni, Ruoming Pang, Mingxing Tan, Martin Wicke, Gang Wu, Shengqi Zhu, Parthasarathy Ranganathan, Norman P. Jouppi
Publikováno v:
Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 3.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7de389f01707c89463c860cb30346d18
https://doi.org/10.1145/3582016.3582049
https://doi.org/10.1145/3582016.3582049
Autor:
Jeffrey Dean, Richard Ho, William Hang, Roger Carpenter, Omkar Pathak, James Laudon, Kavya Srinivasa, Andy Tong, Ebrahim M. Songhori, Quoc V. Le, Joe Wenjie Jiang, Azade Nazi, Anna Goldie, Shen Wang, Azalia Mirhoseini, Young-Joon Lee, Eric Johnson, Jiwoo Pak, Emre Tuncer, Mustafa Yazgan
Publikováno v:
Nature. 594:207-212
Chip floorplanning is the engineering task of designing the physical layout of a computer chip. Despite five decades of research1, chip floorplanning has defied automation, requiring months of intense effort by physical design engineers to produce ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::07f9ab9db4fbd3fe0eba364edde2c0dd
https://doi.org/10.1038/s41586-021-03544-w
https://doi.org/10.1038/s41586-021-03544-w
Autor:
Yingwei Li, Adams Wei Yu, Tianjian Meng, Ben Caine, Jiquan Ngiam, Daiyi Peng, Junyang Shen, Yifeng Lu, Denny Zhou, Quoc V. Le, Alan Yuille, Mingxing Tan
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e7fa8f2c17bd1d388b0cf1d852f09249
https://doi.org/10.1109/cvpr52688.2022.01667
https://doi.org/10.1109/cvpr52688.2022.01667
Autor:
Yu Zhang, Daniel S. Park, Wei Han, James Qin, Anmol Gulati, Joel Shor, Aren Jansen, Yuanzhong Xu, Yanping Huang, Shibo Wang, Zongwei Zhou, Bo Li, Min Ma, William Chan, Jiahui Yu, Yongqiang Wang, Liangliang Cao, Khe Chai Sim, Bhuvana Ramabhadran, Tara N. Sainath, Francoise Beaufays, Zhifeng Chen, Quoc V. Le, Chung-Cheng Chiu, Ruoming Pang, Yonghui Wu
We summarize the results of a host of efforts using giant automatic speech recognition (ASR) models pre-trained using large, diverse unlabeled datasets containing approximately a million hours of audio. We find that the combination of pre-training, s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7dea4e39aabfa465900cf742628eef2c
http://arxiv.org/abs/2109.13226
http://arxiv.org/abs/2109.13226
Despite the fast progress in training specialized models for various tasks, learning a single general model that works well for many tasks is still challenging for computer vision. Here we introduce multi-task self-training (MuST), which harnesses th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c136368262e83d0b6c534f8b1f3c12c7
http://arxiv.org/abs/2108.11353
http://arxiv.org/abs/2108.11353
Publikováno v:
CVPR
We present Meta Pseudo Labels, a semi-supervised learning method that achieves a new state-of-the-art top-1 accuracy of 90.2% on ImageNet, which is 1.6% better than the existing state-of-the-art [16]. Like Pseudo Labels, Meta Pseudo Labels has a teac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d6adad3499b794344ce1371b9d0c93bb
https://doi.org/10.1109/cvpr46437.2021.01139
https://doi.org/10.1109/cvpr46437.2021.01139
Autor:
Chris Alberti, Jennimaria Palomaki, Quoc V. Le, Jakob Uszkoreit, Danielle Epstein, Ankur P. Parikh, Slav Petrov, Kristina Toutanova, Olivia Redfield, Illia Polosukhin, Kenton Lee, Llion Jones, Michael Collins, Ming-Wei Chang, Andrew M. Dai, Matthew Kelcey, Jacob Devlin, Tom Kwiatkowski
Publikováno v:
Transactions of the Association for Computational Linguistics, Vol 7, Pp 453-466 (2019)
We present the Natural Questions corpus, a question answering data set. Questions consist of real anonymized, aggregated queries issued to the Google search engine. An annotator is presented with a question along with a Wikipedia page from the top 5
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::63a711a2e1b76471aebe0fe51dea5eea
https://doi.org/10.1162/tacl_a_00276
https://doi.org/10.1162/tacl_a_00276
Publikováno v:
AAAI
The effort devoted to hand-crafting neural network image classifiers has motivated the use of architecture search to discover them automatically. Although evolutionary algorithms have been repeatedly applied to neural network topologies, the image cl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b5bcec4dc3a4a1c14d34529871495a36
https://doi.org/10.1609/aaai.v33i01.33014780
https://doi.org/10.1609/aaai.v33i01.33014780
Publikováno v:
CVPR
Neural Architecture Search (NAS), together with model scaling, has shown remarkable progress in designing high accuracy and fast convolutional architecture families. However, as neither NAS nor model scaling considers sufficient hardware architecture
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d4cc61c94e8043b0545a5d949b3218d1
Autor:
Azalia Mirhoseini, Anna Goldie, Mustafa Yazgan, Joe Wenjie Jiang, Ebrahim Songhori, Shen Wang, Young-Joon Lee, Eric Johnson, Omkar Pathak, Azade Nazi, Jiwoo Pak, Andy Tong, Kavya Srinivasa, William Hang, Emre Tuncer, Quoc V. Le, James Laudon, Richard Ho, Roger Carpenter, Jeff Dean
Publikováno v:
Nature. 604:E24-E24
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::24c99c871f77c9a7da469877c575b3c9
https://doi.org/10.1038/s41586-022-04657-6
https://doi.org/10.1038/s41586-022-04657-6