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ORCIDChristina Baek
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2020 – today
- 2024
[c8]Christina Baek, J. Zico Kolter, Aditi Raghunathan:
Why is SAM Robust to Label Noise? ICLR 2024- [c7]Yiding Jiang, Christina Baek, J. Zico Kolter:
On the Joint Interaction of Models, Data, and Features. ICLR 2024 - [i8]Aman Mehra, Rahul Saxena, Taeyoun Kim, Christina Baek, Zico Kolter, Aditi Raghunathan:
Predicting the Performance of Foundation Models via Agreement-on-the-Line. CoRR abs/2404.01542 (2024) - [i7]Christina Baek, Zico Kolter, Aditi Raghunathan:
Why is SAM Robust to Label Noise? CoRR abs/2405.03676 (2024) - 2023
- [i6]Yiding Jiang, Christina Baek, J. Zico Kolter:
On the Joint Interaction of Models, Data, and Features. CoRR abs/2306.04793 (2023) - 2022
- [j2]Yuexiang Zhai, Christina Baek, Zhengyuan Zhou, Jiantao Jiao, Yi Ma:
Computational Benefits of Intermediate Rewards for Goal-Reaching Policy Learning. J. Artif. Intell. Res. 73: 847-896 (2022) - [c6]Christina Baek, Ziyang Wu, Kwan Ho Ryan Chan, Tianjiao Ding, Yi Ma, Benjamin D. Haeffele:
Efficient Maximal Coding Rate Reduction by Variational Forms. CVPR 2022: 490-498 - [c5]Yiding Jiang, Vaishnavh Nagarajan, Christina Baek, J. Zico Kolter:
Assessing Generalization of SGD via Disagreement. ICLR 2022 - [c4]Christina Baek, Yiding Jiang, Aditi Raghunathan, J. Zico Kolter:
Agreement-on-the-line: Predicting the Performance of Neural Networks under Distribution Shift. NeurIPS 2022 - [i5]Christina Baek, Ziyang Wu, Kwan Ho Ryan Chan, Tianjiao Ding, Yi Ma, Benjamin D. Haeffele:
Efficient Maximal Coding Rate Reduction by Variational Forms. CoRR abs/2204.00077 (2022) - [i4]Christina Baek, Yiding Jiang, Aditi Raghunathan, Zico Kolter:
Agreement-on-the-Line: Predicting the Performance of Neural Networks under Distribution Shift. CoRR abs/2206.13089 (2022) - 2021
- [c3]Ziyang Wu, Christina Baek, Chong You, Yi Ma:
Incremental Learning via Rate Reduction. CVPR 2021: 1125-1133 - [i3]Yiding Jiang, Vaishnavh Nagarajan, Christina Baek, J. Zico Kolter:
Assessing Generalization of SGD via Disagreement. CoRR abs/2106.13799 (2021) - [i2]Yuexiang Zhai, Christina Baek, Zhengyuan Zhou, Jiantao Jiao, Yi Ma:
Computational Benefits of Intermediate Rewards for Hierarchical Planning. CoRR abs/2107.03961 (2021) - 2020
- [i1]Ziyang Wu, Christina Baek, Chong You, Yi Ma:
Incremental Learning via Rate Reduction. CoRR abs/2011.14593 (2020)
2010 – 2019
- 2018
- [c2]Beom-Jin Lee, Jinyoung Choi, Chung-yeon Lee, Kyung-Wha Park, Sungjun Choi, Cheolho Han, Dong-Sig Han, Christina Baek, Patrick Mokodir Emaase, Byoung-Tak Zhang:
Perception-Action-Learning System for Mobile Social-Service Robots Using Deep Learning. AAAI 2018: 8208-8209 - [c1]Beom-Jin Lee, Jinyoung Choi, Christina Baek, Byoung-Tak Zhang:
Robust Human Following by Deep Bayesian Trajectory Prediction for Home Service Robots. ICRA 2018: 7189-7195 - 2017
- [j1]Ji-Hoon Lee, Seung Hwan Lee, Christina Baek, Hyo-Sun Chun, Je-Hwan Ryu, Jin-Woo Kim, Russell J. Deaton, Byoung-Tak Zhang:
In vitro molecular machine learning algorithm via symmetric internal loops of DNA. Biosyst. 158: 1-9 (2017)
Coauthor Index
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last updated on 2024-08-08 19:18 CEST by the dblp team
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