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2020 – today
- 2023
[i7]Danilo Ribeiro, Omid Abdar, Jack Goetz, Mike Ross, Annie Dong, Kenneth D. Forbus, Ahmed Mohamed:
Towards Zero-Shot Frame Semantic Parsing with Task Agnostic Ontologies and Simple Labels. CoRR abs/2305.03793 (2023)- 2022
- [i6]Shengyuan Hu, Jack Goetz, Kshitiz Malik, Hongyuan Zhan, Zhe Liu, Yue Liu:
FedSynth: Gradient Compression via Synthetic Data in Federated Learning. CoRR abs/2204.01273 (2022) - 2021
- [i5]Pooja Sethi, Denis Savenkov, Forough Arabshahi, Jack Goetz, Micaela Tolliver, Nicolas Scheffer, Ilknur Kabul, Yue Liu, Ahmed Aly:
AutoNLU: Detecting, root-causing, and fixing NLU model errors. CoRR abs/2110.06384 (2021) - 2020
- [j1]Joshua Kammeraad
, Jack Goetz, Eric Walker, Ambuj Tewari, Paul M. Zimmerman:
What Does the Machine Learn? Knowledge Representations of Chemical Reactivity. J. Chem. Inf. Model. 60(3): 1290-1301 (2020) - [i4]Jack Goetz, Ambuj Tewari:
Federated Learning via Synthetic Data. CoRR abs/2008.04489 (2020)
2010 – 2019
- 2019
- [i3]Duc Bui, Kshitiz Malik, Jack Goetz, Honglei Liu, Seungwhan Moon, Anuj Kumar, Kang G. Shin:
Federated User Representation Learning. CoRR abs/1909.12535 (2019) - [i2]Jack Goetz, Kshitiz Malik, Duc Bui, Seungwhan Moon, Honglei Liu, Anuj Kumar:
Active Federated Learning. CoRR abs/1909.12641 (2019) - [i1]Jack Goetz, Ambuj Tewari:
Not All are Made Equal: Consistency of Weighted Averaging Estimators Under Active Learning. CoRR abs/1910.05321 (2019) - 2018
- [c2]Jack Goetz, Ambuj Tewari, Paul M. Zimmerman:
Active Learning for Non-Parametric Regression Using Purely Random Trees. NeurIPS 2018: 2542-2551 - 2017
- [c1]Young Hun Jung, Jack Goetz, Ambuj Tewari:
Online multiclass boosting. NIPS 2017: 919-928
Coauthor Index
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