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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), 1-12, 2022
152022
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
102022
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
102019
GIST: Distributed training for large-scale graph convolutional networks
CR Wolfe, J Yang, A Chowdhury, C Dun, A Bayer, S Segarra, A Kyrillidis
arXiv preprint arXiv:2102.10424, 2021
42021
Demon: Momentum Decay for Improved Neural Network Training
J Chen, C Wolfe, Z Li, A Kyrillidis
42020
E-Stitchup: Data Augmentation for Pre-Trained Embeddings
CR Wolfe, KT Lundgaard
arXiv preprint arXiv:1912.00772, 2019
42019
Data Augmentation for Deep Transfer Learning
CR Wolfe, KT Lundgaard
32019
ResIST: Layer-wise decomposition of ResNets for distributed training
C Dun, CR Wolfe, CM Jermaine, A Kyrillidis
Uncertainty in Artificial Intelligence, 610-620, 2022
22022
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
22022
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
22019
Demon: Momentum Decay for Improved Neural Network Training. arXiv e-prints, Article
J Chen, C Wolfe, Z Li, A Kyrillidis
arXiv preprint arXiv:1910.04952, 2019
22019
REX: Revisiting Budgeted Training with an Improved Schedule
J Chen, C Wolfe, T Kyrillidis
Proceedings of Machine Learning and Systems 4, 64-76, 2022
12022
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), 1581-1590, 2022
12022
Provably efficient lottery ticket discovery
CR Wolfe, Q Wang, JL Kim, A Kyrillidis
arXiv preprint arXiv:2108.00259, 2021
12021
Exceeding the Limits of Visual-Linguistic Multi-Task Learning
CR Wolfe, KT Lundgaard
arXiv preprint arXiv:2107.13054, 2021
12021
Cold Start Streaming Learning for Deep Networks
CR Wolfe, A Kyrillidis
arXiv preprint arXiv:2211.04624, 2022
2022
Estimating product attribute preferences
A Kushkuley, K Lundgaard, C Wolfe
US Patent App. 17/230,257, 2022
2022
Systems and methods of data augmentation for pre-trained embeddings
K Lundgaard, C Wolfe
US Patent 11,461,537, 2022
2022
Exceeding the limits of visual-linguistic multi-task learning
C Wolfe, K Lundgaard
US Patent App. 17/485,985, 2022
2022
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
2022
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