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Yiding Jiang
Yiding Jiang
PhD Student, Carnegie Mellon University
Подтвержден адрес электронной почты в домене cs.cmu.edu - Главная страница
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Год
Fantastic Generalization Measures and Where to Find Them
Y Jiang, B Neyshabur, H Mobahi, D Krishnan, S Bengio
International Conference on Learning Representations, 2019
6302019
Language as an Abstraction for Hierarchical Deep Reinforcement Learning
Y Jiang, S Gu, K Murphy, C Finn
Advances in Neural Information Processing Systems, 2019
2402019
Predicting the generalization gap in deep networks with margin distributions
Y Jiang, D Krishnan, H Mobahi, S Bengio
International Conference on Learning Representations, 2018
2232018
Observational Overfitting in Reinforcement Learning
X Song, Y Jiang, S Tu, Y Du, B Neyshabur
International Conference on Learning Representations, 2020
1482020
Assessing generalization of sgd via disagreement
Y Jiang, V Nagarajan, C Baek, JZ Kolter
International Conference on Learning Representations, 2021
1172021
Agreement-on-the-line: Predicting the performance of neural networks under distribution shift
C Baek, Y Jiang, A Raghunathan, JZ Kolter
Advances in Neural Information Processing Systems 35, 19274-19289, 2022
652022
Neurips 2020 competition: Predicting generalization in deep learning
Y Jiang, P Foret, S Yak, DM Roy, H Mobahi, GK Dziugaite, S Bengio, ...
arXiv preprint arXiv:2012.07976, 2020
582020
Adversarial grasp objects
D Wang, D Tseng, P Li, Y Jiang, M Guo, M Danielczuk, J Mahler, ...
2019 IEEE 15th International Conference on Automation Science and …, 2019
322019
Permutation equivariant neural functionals
A Zhou, K Yang, K Burns, A Cardace, Y Jiang, S Sokota, JZ Kolter, C Finn
Advances in neural information processing systems 36, 2024
292024
Methods and analysis of the first competition in predicting generalization of deep learning
Y Jiang, P Natekar, M Sharma, SK Aithal, D Kashyap, N Subramanyam, ...
NeurIPS 2020 Competition and Demonstration Track, 170-190, 2021
262021
On the importance of exploration for generalization in reinforcement learning
Y Jiang, JZ Kolter, R Raileanu
Advances in Neural Information Processing Systems 36, 2024
22*2024
Neural functional transformers
A Zhou, K Yang, Y Jiang, K Burns, W Xu, S Sokota, JZ Kolter, C Finn
Advances in neural information processing systems 36, 2024
172024
Language models are weak learners
H Manikandan, Y Jiang, JZ Kolter
Advances in Neural Information Processing Systems 36, 50907-50931, 2023
132023
Learning options via compression
Y Jiang, E Liu, B Eysenbach, JZ Kolter, C Finn
Advances in Neural Information Processing Systems 35, 21184-21199, 2022
132022
Understanding prompt engineering may not require rethinking generalization
V Akinwande, Y Jiang, D Sam, JZ Kolter
arXiv preprint arXiv:2310.03957, 2023
42023
Automated Black-box Prompt Engineering for Personalized Text-to-Image Generation
Y He, A Robey, N Murata, Y Jiang, J Williams, GJ Pappas, H Hassani, ...
arXiv preprint arXiv:2403.19103, 2024
22024
Ask & Explore: Grounded Question Answering for Curiosity-Driven Exploration
JN Kaur, Y Jiang, PP Liang
arXiv preprint arXiv:2104.11902, 2021
22021
On the Joint Interaction of Models, Data, and Features
Y Jiang, C Baek, JZ Kolter
arXiv preprint arXiv:2306.04793, 2023
12023
Performance of neural networks under distribution shift
Y Jiang, C Baek, J Kolter, A Raghunathan, JD Semedo, FJC CONDESSA, ...
US Patent App. 17/841,120, 2023
2023
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Статьи 1–19