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Cameron Wolfe
Cameron Wolfe
PhD Student, Rice University
Verified email at rice.edu
Title
Cited by
Cited by
Year
Current progress and open challenges for applying deep learning across the biosciences
N Sapoval, A Aghazadeh, MG Nute, DA Antunes, A Balaji, R Baraniuk, ...
Nature Communications 13 (1), 1728, 2022
1372022
PipeGCN: Efficient full-graph training of graph convolutional networks with pipelined feature communication
C Wan, Y Li, CR Wolfe, A Kyrillidis, NS Kim, Y Lin
arXiv preprint arXiv:2203.10428, 2022
502022
Distributed learning of fully connected neural networks using independent subnet training
B Yuan, CR Wolfe, C Dun, Y Tang, A Kyrillidis, C Jermaine
Proceedings of the VLDB Endowment 15 (8), 2022
252022
Distributed learning of deep neural networks using independent subnet training
B Yuan, CR Wolfe, C Dun, Y Tang, A Kyrillidis, CM Jermaine
arXiv preprint arXiv:1910.02120, 2019
192019
ResIST: Layer-wise decomposition of resnets for distributed training
C Dun, CR Wolfe, CM Jermaine, A Kyrillidis
Uncertainty in Artificial Intelligence, 610-620, 2022
172022
Demon: improved neural network training with momentum decay
J Chen, C Wolfe, Z Li, A Kyrillidis
ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022
172022
GIST: Distributed training for large-scale graph convolutional networks
CR Wolfe, J Yang, F Liao, A Chowdhury, C Dun, A Bayer, S Segarra, ...
Journal of Applied and Computational Topology, 1-53, 2023
122023
Rex: Revisiting budgeted training with an improved schedule
J Chen, C Wolfe, T Kyrillidis
Proceedings of Machine Learning and Systems 4, 64-76, 2022
92022
E-stitchup: Data augmentation for pre-trained embeddings
CR Wolfe, KT Lundgaard
arXiv preprint arXiv:1912.00772, 2019
72019
Systems and methods of data augmentation for pre-trained embeddings
K Lundgaard, C Wolfe
US Patent 11,461,537, 2022
62022
Method and system utilizing ontological machine learning for labeling products in an electronic product catalog
K Lundgaard, C Wolfe
US Patent 11,361,362, 2022
62022
Demon: Momentum decay for improved neural network training
J Chen, C Wolfe, Z Li, A Kyrillidis
42020
Data augmentation for deep transfer learning
CR Wolfe, KT Lundgaard
arXiv preprint arXiv:1912.00772, 2019
42019
Exceeding the limits of visual-linguistic multi-task learning
CR Wolfe, KT Lundgaard
arXiv preprint arXiv:2107.13054, 2021
32021
Functional generative design of mechanisms with recurrent neural networks and novelty search
CR Wolfe, CC Tutum, R Miikkulainen
Proceedings of the Genetic and Evolutionary Computation Conference, 1373-1380, 2019
32019
Cold start streaming learning for deep networks
CR Wolfe, A Kyrillidis
arXiv preprint arXiv:2211.04624, 2022
22022
How much pre-training is enough to discover a good subnetwork?
CR Wolfe, Q Wang, JL Kim, A Kyrillidis
22021
Provably efficient lottery ticket discovery
CR Wolfe, Q Wang, JL Kim, A Kyrillidis
arXiv preprint arXiv:2108.00259, 2021
22021
i-SpaSP: Structured Neural Pruning via Sparse Signal Recovery
CR Wolfe, A Kyrillidis
Learning for Dynamics and Control Conference, 248-262, 2022
12022
Exceeding the limits of visual-linguistic multi-task learning
C Wolfe, K Lundgaard
US Patent 11,915,471, 2024
2024
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