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Jack Goetz
Jack Goetz
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Title
Cited by
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Year
Active federated learning
J Goetz, K Malik, D Bui, S Moon, H Liu, A Kumar
arXiv preprint arXiv:1909.12641, 2019
492019
Online multiclass boosting
YH Jung, J Goetz, A Tewari
Advances in neural information processing systems 30, 2017
292017
Federated user representation learning
D Bui, K Malik, J Goetz, H Liu, S Moon, A Kumar, KG Shin
arXiv preprint arXiv:1909.12535, 2019
252019
What does the machine learn? Knowledge representations of chemical reactivity
JA Kammeraad, J Goetz, EA Walker, A Tewari, PM Zimmerman
Journal of chemical information and modeling 60 (3), 1290-1301, 2020
182020
Active learning for non-parametric regression using purely random trees
J Goetz, A Tewari, P Zimmerman
Advances in Neural Information Processing Systems 31, 2018
152018
Federated learning via synthetic data
J Goetz, A Tewari
arXiv preprint arXiv:2008.04489, 2020
132020
Learning from others without sacrificing privacy: Simulation comparing centralized and federated machine learning on mobile health data
JC Liu, J Goetz, S Sen, A Tewari
JMIR mHealth and uHealth 9 (3), e23728, 2021
62021
Mining events with declassified diplomatic documents
Y Gao, J Goetz, M Connelly, R Mazumder
The Annals of Applied Statistics 14 (4), 1699-1723, 2020
22020
Not all are made equal: Consistency of weighted averaging estimators under active learning
J Goetz, A Tewari
arXiv preprint arXiv:1910.05321, 2019
12019
FedSynth: Gradient Compression via Synthetic Data in Federated Learning
S Hu, J Goetz, K Malik, H Zhan, Z Liu, Y Liu
arXiv preprint arXiv:2204.01273, 2022
2022
AutoNLU: Detecting, root-causing, and fixing NLU model errors
P Sethi, D Savenkov, F Arabshahi, J Goetz, M Tolliver, N Scheffer, I Kabul, ...
arXiv preprint arXiv:2110.06384, 2021
2021
Understanding the limits of machines in learning chemical reactivity
J Kammeraad, J Goetz, E Walker, A Tewari, P Zimmerman
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY 257, 2019
2019
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P Sethi, D Savenkov, F Arabshahi, J Goetz, M Tolliver, N Scheffer, I Kabul, ...
Active Federated Learning Download PDF Open Website
J Goetz, K Malik, D Bui, S Moon, H Liu, A Kumar
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