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2020 – today
- 2023
[i24]Sheng Shen, Le Hou, Yanqi Zhou, Nan Du, Shayne Longpre, Jason Wei, Hyung Won Chung, Barret Zoph, William Fedus, Xinyun Chen, Tu Vu, Yuexin Wu, Wuyang Chen, Albert Webson, Yunxuan Li, Vincent Zhao, Hongkun Yu, Kurt Keutzer, Trevor Darrell, Denny Zhou:
Flan-MoE: Scaling Instruction-Finetuned Language Models with Sparse Mixture of Experts. CoRR abs/2305.14705 (2023)- 2022
- [j2]William Fedus, Barret Zoph, Noam Shazeer:
Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity. J. Mach. Learn. Res. 23: 120:1-120:39 (2022) - [j1]Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus:
Emergent Abilities of Large Language Models. Trans. Mach. Learn. Res. 2022 (2022) - [c12]Yi Tay, Mostafa Dehghani, Jinfeng Rao, William Fedus, Samira Abnar, Hyung Won Chung, Sharan Narang, Dani Yogatama, Ashish Vaswani, Donald Metzler:
Scale Efficiently: Insights from Pretraining and Finetuning Transformers. ICLR 2022 - [c11]Nan Du, Yanping Huang, Andrew M. Dai, Simon Tong, Dmitry Lepikhin, Yuanzhong Xu, Maxim Krikun, Yanqi Zhou, Adams Wei Yu, Orhan Firat, Barret Zoph, Liam Fedus, Maarten P. Bosma, Zongwei Zhou, Tao Wang, Yu Emma Wang, Kellie Webster, Marie Pellat, Kevin Robinson, Kathleen S. Meier-Hellstern, Toju Duke, Lucas Dixon, Kun Zhang, Quoc V. Le, Yonghui Wu, Zhifeng Chen, Claire Cui:
GLaM: Efficient Scaling of Language Models with Mixture-of-Experts. ICML 2022: 5547-5569 - [i23]Barret Zoph, Irwan Bello, Sameer Kumar, Nan Du, Yanping Huang, Jeff Dean, Noam Shazeer, William Fedus:
Designing Effective Sparse Expert Models. CoRR abs/2202.08906 (2022) - [i22]Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, Noah Fiedel:
PaLM: Scaling Language Modeling with Pathways. CoRR abs/2204.02311 (2022) - [i21]Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus:
Emergent Abilities of Large Language Models. CoRR abs/2206.07682 (2022) - [i20]Yi Tay, Mostafa Dehghani, Samira Abnar, Hyung Won Chung, William Fedus, Jinfeng Rao, Sharan Narang, Vinh Q. Tran, Dani Yogatama, Donald Metzler:
Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling? CoRR abs/2207.10551 (2022) - [i19]William Fedus, Jeff Dean, Barret Zoph:
A Review of Sparse Expert Models in Deep Learning. CoRR abs/2209.01667 (2022) - [i18]Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Y. Zhao, Yanping Huang, Andrew M. Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, Jason Wei:
Scaling Instruction-Finetuned Language Models. CoRR abs/2210.11416 (2022) - 2021
- [c10]Sharan Narang, Hyung Won Chung, Yi Tay, Liam Fedus, Thibault Févry, Michael Matena, Karishma Malkan, Noah Fiedel, Noam Shazeer, Zhenzhong Lan, Yanqi Zhou, Wei Li, Nan Ding, Jake Marcus, Adam Roberts, Colin Raffel:
Do Transformer Modifications Transfer Across Implementations and Applications? EMNLP (1) 2021: 5758-5773 - [c9]Irwan Bello, William Fedus, Xianzhi Du, Ekin Dogus Cubuk, Aravind Srinivas, Tsung-Yi Lin, Jonathon Shlens, Barret Zoph:
Revisiting ResNets: Improved Training and Scaling Strategies. NeurIPS 2021: 22614-22627 - [i17]William Fedus, Barret Zoph, Noam Shazeer:
Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity. CoRR abs/2101.03961 (2021) - [i16]Sharan Narang, Hyung Won Chung, Yi Tay, William Fedus, Thibault Févry, Michael Matena, Karishma Malkan, Noah Fiedel, Noam Shazeer, Zhenzhong Lan, Yanqi Zhou, Wei Li, Nan Ding, Jake Marcus, Adam Roberts, Colin Raffel:
Do Transformer Modifications Transfer Across Implementations and Applications? CoRR abs/2102.11972 (2021) - [i15]Irwan Bello, William Fedus, Xianzhi Du, Ekin D. Cubuk, Aravind Srinivas, Tsung-Yi Lin, Jonathon Shlens, Barret Zoph:
Revisiting ResNets: Improved Training and Scaling Strategies. CoRR abs/2103.07579 (2021) - [i14]Yi Tay, Mostafa Dehghani, Jinfeng Rao, William Fedus, Samira Abnar, Hyung Won Chung, Sharan Narang, Dani Yogatama, Ashish Vaswani, Donald Metzler:
Scale Efficiently: Insights from Pre-training and Fine-tuning Transformers. CoRR abs/2109.10686 (2021) - [i13]Adrien Ali Taïga, William Fedus, Marlos C. Machado, Aaron C. Courville, Marc G. Bellemare:
On Bonus-Based Exploration Methods in the Arcade Learning Environment. CoRR abs/2109.11052 (2021) - [i12]Nan Du, Yanping Huang, Andrew M. Dai, Simon Tong, Dmitry Lepikhin, Yuanzhong Xu, Maxim Krikun, Yanqi Zhou, Adams Wei Yu, Orhan Firat, Barret Zoph, Liam Fedus, Maarten Bosma, Zongwei Zhou, Tao Wang, Yu Emma Wang, Kellie Webster, Marie Pellat, Kevin Robinson, Kathy Meier-Hellstern, Toju Duke, Lucas Dixon, Kun Zhang, Quoc V. Le, Yonghui Wu, Zhifeng Chen, Claire Cui:
GLaM: Efficient Scaling of Language Models with Mixture-of-Experts. CoRR abs/2112.06905 (2021) - 2020
- [c8]Vishal Jain, William Fedus, Hugo Larochelle, Doina Precup, Marc G. Bellemare:
Algorithmic Improvements for Deep Reinforcement Learning Applied to Interactive Fiction. AAAI 2020: 4328-4336 - [c7]Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, Laurent Charlin:
Language GANs Falling Short. ICLR 2020 - [c6]Adrien Ali Taïga, William Fedus, Marlos C. Machado
, Aaron C. Courville, Marc G. Bellemare:
On Bonus Based Exploration Methods In The Arcade Learning Environment. ICLR 2020 - [c5]William Fedus, Prajit Ramachandran, Rishabh Agarwal, Yoshua Bengio, Hugo Larochelle, Mark Rowland, Will Dabney:
Revisiting Fundamentals of Experience Replay. ICML 2020: 3061-3071 - [i11]William Fedus, Dibya Ghosh, John D. Martin, Marc G. Bellemare, Yoshua Bengio, Hugo Larochelle:
On Catastrophic Interference in Atari 2600 Games. CoRR abs/2002.12499 (2020) - [i10]William Fedus, Prajit Ramachandran, Rishabh Agarwal, Yoshua Bengio, Hugo Larochelle, Mark Rowland, Will Dabney:
Revisiting Fundamentals of Experience Replay. CoRR abs/2007.06700 (2020)
2010 – 2019
- 2019
- [c4]Anirudh Goyal, Philemon Brakel, William Fedus, Soumye Singhal, Timothy P. Lillicrap, Sergey Levine, Hugo Larochelle, Yoshua Bengio:
Recall Traces: Backtracking Models for Efficient Reinforcement Learning. ICLR (Poster) 2019 - [c3]Petar Velickovic, William Fedus, William L. Hamilton, Pietro Liò, Yoshua Bengio, R. Devon Hjelm:
Deep Graph Infomax. ICLR (Poster) 2019 - [i9]William Fedus, Carles Gelada, Yoshua Bengio, Marc G. Bellemare, Hugo Larochelle:
Hyperbolic Discounting and Learning over Multiple Horizons. CoRR abs/1902.06865 (2019) - [i8]Adrien Ali Taïga, William Fedus, Marlos C. Machado, Aaron C. Courville, Marc G. Bellemare:
Benchmarking Bonus-Based Exploration Methods on the Arcade Learning Environment. CoRR abs/1908.02388 (2019) - [i7]Vishal Jain, William Fedus, Hugo Larochelle, Doina Precup, Marc G. Bellemare:
Algorithmic Improvements for Deep Reinforcement Learning applied to Interactive Fiction. CoRR abs/1911.12511 (2019) - 2018
- [c2]William Fedus, Ian J. Goodfellow, Andrew M. Dai:
MaskGAN: Better Text Generation via Filling in the _______. ICLR (Poster) 2018 - [c1]William Fedus, Mihaela Rosca, Balaji Lakshminarayanan, Andrew M. Dai, Shakir Mohamed, Ian J. Goodfellow:
Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step. ICLR (Poster) 2018 - [i6]William Fedus, Ian J. Goodfellow, Andrew M. Dai:
MaskGAN: Better Text Generation via Filling in the ______. CoRR abs/1801.07736 (2018) - [i5]Valentin Thomas, Emmanuel Bengio, William Fedus, Jules Pondard, Philippe Beaudoin, Hugo Larochelle, Joelle Pineau, Doina Precup, Yoshua Bengio:
Disentangling the independently controllable factors of variation by interacting with the world. CoRR abs/1802.09484 (2018) - [i4]Anirudh Goyal, Philemon Brakel, William Fedus, Timothy P. Lillicrap, Sergey Levine, Hugo Larochelle, Yoshua Bengio:
Recall Traces: Backtracking Models for Efficient Reinforcement Learning. CoRR abs/1804.00379 (2018) - [i3]Petar Velickovic, William Fedus, William L. Hamilton, Pietro Liò, Yoshua Bengio, R. Devon Hjelm:
Deep Graph Infomax. CoRR abs/1809.10341 (2018) - [i2]Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, Laurent Charlin:
Language GANs Falling Short. CoRR abs/1811.02549 (2018) - 2017
- [i1]William Fedus, Mihaela Rosca, Balaji Lakshminarayanan, Andrew M. Dai, Shakir Mohamed, Ian J. Goodfellow:
Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step. CoRR abs/1710.08446 (2017)
Coauthor Index
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last updated on 2023-10-02 01:17 CEST by the dblp team
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