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2020 – today
- 2023
[c4]Jane H. Lee, Saeid Haghighatshoar, Amin Karbasi:
Exact Gradient Computation for Spiking Neural Networks via Forward Propagation. AISTATS 2023: 1812-1831- [c3]Jane H. Lee, Andre Wibisono, Emmanouil Zampetakis:
Learning Exponential Families from Truncated Samples. NeurIPS 2023 - 2022
- [i2]Jane H. Lee, Saeid Haghighatshoar, Amin Karbasi:
Exact Gradient Computation for Spiking Neural Networks Through Forward Propagation. CoRR abs/2210.15415 (2022) - 2021
- [j1]Kokil Jaidka
, Sharath Chandra Guntuku, Jane H. Lee, Zhengyi Luo, Anneke Buffone, Lyle H. Ungar:
The rural-urban stress divide: Obtaining geographical insights through Twitter. Comput. Hum. Behav. 114: 106544 (2021) - [c2]Mingyuan Zhang, Jane H. Lee, Shivani Agarwal:
Learning from Noisy Labels with No Change to the Training Process. ICML 2021: 12468-12478 - 2020
- [c1]Shuxiao Chen, Edgar Dobriban, Jane H. Lee:
A Group-Theoretic Framework for Data Augmentation. NeurIPS 2020
2010 – 2019
- 2019
- [i1]Shuxiao Chen, Edgar Dobriban, Jane H. Lee:
Invariance reduces Variance: Understanding Data Augmentation in Deep Learning and Beyond. CoRR abs/1907.10905 (2019)
Coauthor Index
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