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ORCIDCameron R. Wolfe
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Journal Articles
- 2024
[j4]Cameron R. Wolfe
, Jingkang Yang, Fangshuo Liao, Arindam Chowdhury, Chen Dun, Artun Bayer, Santiago Segarra, Anastasios Kyrillidis:
GIST: distributed training for large-scale graph convolutional networks. J. Appl. Comput. Topol. 8(5): 1363-1415 (2024)- [j3]Cameron R. Wolfe, Anastasios Kyrillidis:
Better schedules for low precision training of deep neural networks. Mach. Learn. 113(6): 3569-3587 (2024) - [j2]Cameron R. Wolfe, Fangshuo Liao, Qihan Wang, Junhyung Lyle Kim, Anastasios Kyrillidis:
How Much Pre-training Is Enough to Discover a Good Subnetwork? Trans. Mach. Learn. Res. 2024 (2024) - 2022
- [j1]Binhang Yuan, Cameron R. Wolfe, Chen Dun, Yuxin Tang, Anastasios Kyrillidis, Chris Jermaine:
Distributed Learning of Fully Connected Neural Networks using Independent Subnet Training. Proc. VLDB Endow. 15(8): 1581-1590 (2022)
Conference and Workshop Papers
- 2022
- [c6]John Chen, Cameron R. Wolfe, Zhao Li, Anastasios Kyrillidis:
Demon: Improved Neural Network Training With Momentum Decay. ICASSP 2022: 3958-3962 - [c5]Cheng Wan, Youjie Li, Cameron R. Wolfe, Anastasios Kyrillidis, Nam Sung Kim, Yingyan Lin:
PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication. ICLR 2022 - [c4]Cameron R. Wolfe, Anastasios Kyrillidis:
i-SpaSP: Structured Neural Pruning via Sparse Signal Recovery. L4DC 2022: 248-262 - [c3]John Chen, Cameron R. Wolfe, Tasos Kyrillidis:
REX: Revisiting Budgeted Training with an Improved Schedule. MLSys 2022 - [c2]Chen Dun, Cameron R. Wolfe, Christopher M. Jermaine, Anastasios Kyrillidis:
ResIST: Layer-wise decomposition of ResNets for distributed training. UAI 2022: 610-620 - 2019
- [c1]Cameron R. Wolfe, Cem Celal Tutum, Risto Miikkulainen:
Functional generative design of mechanisms with recurrent neural networks and novelty search. GECCO 2019: 1373-1380
Informal and Other Publications
- 2024
- [i12]Cameron R. Wolfe, Anastasios Kyrillidis:
Better Schedules for Low Precision Training of Deep Neural Networks. CoRR abs/2403.02243 (2024) - 2022
- [i11]Cheng Wan, Youjie Li, Cameron R. Wolfe, Anastasios Kyrillidis, Nam Sung Kim, Yingyan Lin:
PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication. CoRR abs/2203.10428 (2022) - [i10]Cameron R. Wolfe, Anastasios Kyrillidis:
Cold Start Streaming Learning for Deep Networks. CoRR abs/2211.04624 (2022) - 2021
- [i9]Cameron R. Wolfe, Jingkang Yang, Arindam Chowdhury, Chen Dun, Artun Bayer, Santiago Segarra, Anastasios Kyrillidis:
GIST: Distributed Training for Large-Scale Graph Convolutional Networks. CoRR abs/2102.10424 (2021) - [i8]Junhyung Lyle Kim, Jose Antonio Lara Benitez, Mohammad Taha Toghani, Cameron R. Wolfe, Zhiwei Zhang, Anastasios Kyrillidis:
Momentum-inspired Low-Rank Coordinate Descent for Diagonally Constrained SDPs. CoRR abs/2106.08775 (2021) - [i7]Chen Dun, Cameron R. Wolfe, Christopher M. Jermaine, Anastasios Kyrillidis:
ResIST: Layer-Wise Decomposition of ResNets for Distributed Training. CoRR abs/2107.00961 (2021) - [i6]John Chen, Cameron R. Wolfe, Anastasios Kyrillidis:
REX: Revisiting Budgeted Training with an Improved Schedule. CoRR abs/2107.04197 (2021) - [i5]Cameron R. Wolfe, Keld T. Lundgaard:
Exceeding the Limits of Visual-Linguistic Multi-Task Learning. CoRR abs/2107.13054 (2021) - [i4]Cameron R. Wolfe, Qihan Wang, Junhyung Lyle Kim, Anastasios Kyrillidis:
Provably Efficient Lottery Ticket Discovery. CoRR abs/2108.00259 (2021) - [i3]Cameron R. Wolfe, Anastasios Kyrillidis:
i-SpaSP: Structured Neural Pruning via Sparse Signal Recovery. CoRR abs/2112.04905 (2021) - 2019
- [i2]Cameron R. Wolfe, Cem Celal Tutum, Risto Miikkulainen:
Functional Generative Design of Mechanisms with Recurrent Neural Networks and Novelty Search. CoRR abs/1903.10103 (2019) - [i1]Cameron R. Wolfe, Keld T. Lundgaard:
Data Augmentation for Deep Transfer Learning. CoRR abs/1912.00772 (2019)
Coauthor Index
aka: Tasos Kyrillidis
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