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ORCIDTaejong Joo
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2020 – today
- 2024
[c3]Taejong Joo, Diego Klabjan:
IW-GAE: Importance weighted group accuracy estimation for improved calibration and model selection in unsupervised domain adaptation. ICML 2024- 2023
- [i4]Taejong Joo, Diego Klabjan:
IW-GAE: Importance weighted group accuracy estimation for improved calibration and model selection in unsupervised domain adaptation. CoRR abs/2310.10611 (2023) - 2020
- [c2]Taejong Joo, Donggu Kang, Byunghoon Kim:
Regularizing activations in neural networks via distribution matching with the Wasserstein metric. ICLR 2020 - [c1]Taejong Joo, Uijung Chung, Min-Gwan Seo:
Being Bayesian about Categorical Probability. ICML 2020: 4950-4961 - [i3]Taejong Joo, Donggu Kang, Byunghoon Kim:
Regularizing activations in neural networks via distribution matching with the Wasserstein metric. CoRR abs/2002.05366 (2020) - [i2]Taejong Joo, Uijung Chung, Min-Gwan Seo:
Being Bayesian about Categorical Probability. CoRR abs/2002.07965 (2020) - [i1]Taejong Joo, Uijung Chung:
Deep Learning Requires Explicit Regularization for Reliable Predictive Probability. CoRR abs/2006.06399 (2020)
2010 – 2019
- 2019
- [j2]Taejong Joo, Minji Seo, Dongmin Shin
:
An adaptive approach for determining batch sizes using the hidden Markov model. J. Intell. Manuf. 30(2): 917-932 (2019) - [j1]Taejong Joo, Dongmin Shin:
Formalizing Human-Machine Interactions for Adaptive Automation in Smart Manufacturing. IEEE Trans. Hum. Mach. Syst. 49(6): 529-539 (2019)
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