Yiding Jiang

According to our database, Yiding Jiang authored at least 22 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws.

Yiding Jiang, Allan Zhou, Zhili Feng, Sadhika Malladi, J. Zico Kolter

CoRR, 2024

Improving Generalization on the ProcGen Benchmark with Simple Architectural Changes and Scale.

Andrew Jesson, Yiding Jiang

CoRR, 2024

Automated Black-box Prompt Engineering for Personalized Text-to-Image Generation.

Yutong He, Alexander Robey, Naoki Murata, Yiding Jiang, Joshua Williams, George J. Pappas, Hamed Hassani, Yuki Mitsufuji, Ruslan Salakhutdinov, J. Zico Kolter

CoRR, 2024

On the Joint Interaction of Models, Data, and Features.

Yiding Jiang, Christina Baek, J. Zico Kolter

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Understanding prompt engineering may not require rethinking generalization.

Victor Akinwande, Yiding Jiang, Dylan Sam, J. Zico Kolter

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Permutation Equivariant Neural Functionals.

Allan Zhou, Kaien Yang, Kaylee Burns, Yiding Jiang, Samuel Sokota, J. Zico Kolter, Chelsea Finn

CoRR, 2023

A Wavelet Decomposition Network Based Edge Monitoring System for Classification of Electrical Equipment.

Xianchen Wang, Di Cao, Yiding Jiang, Yanjing Lei, Linghao Ying

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2023

Neural Functional Transformers.

Allan Zhou, Kaien Yang, Yiding Jiang, Kaylee Burns, Winnie Xu, Samuel Sokota, J. Zico Kolter, Chelsea Finn

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Permutation Equivariant Neural Functionals.

Allan Zhou, Kaien Yang, Kaylee Burns, Adriano Cardace, Yiding Jiang, Samuel Sokota, J. Zico Kolter, Chelsea Finn

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Language Models are Weak Learners.

Hariharan Manikandan, Yiding Jiang, J. Zico Kolter

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On the Importance of Exploration for Generalization in Reinforcement Learning.

Yiding Jiang, J. Zico Kolter, Roberta Raileanu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Learning Options via Compression.

Yiding Jiang, Evan Zheran Liu, Benjamin Eysenbach, J. Zico Kolter, Chelsea Finn

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Agreement-on-the-line: Predicting the Performance of Neural Networks under Distribution Shift.

Christina Baek, Yiding Jiang, Aditi Raghunathan, J. Zico Kolter

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Assessing Generalization of SGD via Disagreement.

Yiding Jiang, Vaishnavh Nagarajan, Christina Baek, J. Zico Kolter

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Ask & Explore: Grounded Question Answering for Curiosity-Driven Exploration.

Jivat Neet Kaur, Yiding Jiang, Paul Pu Liang

CoRR, 2021

2020

NeurIPS 2020 Competition: Predicting Generalization in Deep Learning.

Yiding Jiang, Pierre Foret, Scott Yak, Daniel M. Roy, Hossein Mobahi, Gintare Karolina Dziugaite, Samy Bengio, Suriya Gunasekar, Isabelle Guyon, Behnam Neyshabur

CoRR, 2020

Methods and Analysis of The First Competition in Predicting Generalization of Deep Learning.

Yiding Jiang, Parth Natekar, Manik Sharma, Sumukh K. Aithal, Dhruva Kashyap, Natarajan Subramanyam, Carlos Lassance, Daniel M. Roy, Gintare Karolina Dziugaite, Suriya Gunasekar, Isabelle Guyon, Pierre Foret, Scott Yak, Hossein Mobahi, Behnam Neyshabur, Samy Bengio

Proceedings of the NeurIPS 2020 Competition and Demonstration Track, 2020

Observational Overfitting in Reinforcement Learning.

Xingyou Song, Yiding Jiang, Stephen Tu, Yilun Du, Behnam Neyshabur

Proceedings of the 8th International Conference on Learning Representations, 2020

Fantastic Generalization Measures and Where to Find Them.

Yiding Jiang, Behnam Neyshabur, Hossein Mobahi, Dilip Krishnan, Samy Bengio

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Language as an Abstraction for Hierarchical Deep Reinforcement Learning.

Yiding Jiang, Shixiang Gu, Kevin Murphy, Chelsea Finn

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Predicting the Generalization Gap in Deep Networks with Margin Distributions.

Yiding Jiang, Dilip Krishnan, Hossein Mobahi, Samy Bengio

Proceedings of the 7th International Conference on Learning Representations, 2019

Adversarial Grasp Objects.

David Wang, David Tseng, Pusong Li, Yiding Jiang, Menglong Guo, Michael Danielczuk, Jeffrey Mahler, Jeffrey Ichnowski, Ken Goldberg

Proceedings of the 15th IEEE International Conference on Automation Science and Engineering, 2019