Jeff Z. HaoChen

According to our database, Jeff Z. HaoChen authored at least 12 papers between 2019 and 2023.

Collaborative distances:

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

2023

Beyond NTK with Vanilla Gradient Descent: A Mean-Field Analysis of Neural Networks with Polynomial Width, Samples, and Time.

Arvind Mahankali, Jeff Z. HaoChen, Kefan Dong, Margalit Glasgow, Tengyu Ma

CoRR, 2023

Diagnosing and Rectifying Vision Models using Language.

Yuhui Zhang, Jeff Z. HaoChen, Shih-Cheng Huang, Kuan-Chieh Wang, James Zou, Serena Yeung

Proceedings of the Eleventh International Conference on Learning Representations, 2023

A theoretical study of inductive biases in contrastive learning.

Jeff Z. HaoChen, Tengyu Ma

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models.

Yuhui Zhang, Michihiro Yasunaga, Zhengping Zhou, Jeff Z. HaoChen, James Zou, Percy Liang, Serena Yeung

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

Beyond Separability: Analyzing the Linear Transferability of Contrastive Representations to Related Subpopulations.

Jeff Z. HaoChen, Colin Wei, Ananya Kumar, Tengyu Ma

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

Amortized Proximal Optimization.

Juhan Bae, Paul Vicol, Jeff Z. HaoChen, Roger B. Grosse

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

Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation.

Kendrick Shen, Robbie M. Jones, Ananya Kumar, Sang Michael Xie, Jeff Z. HaoChen, Tengyu Ma, Percy Liang

Proceedings of the International Conference on Machine Learning, 2022

Self-supervised Learning is More Robust to Dataset Imbalance.

Hong Liu, Jeff Z. HaoChen, Adrien Gaidon, Tengyu Ma

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss.

Jeff Z. HaoChen, Colin Wei, Adrien Gaidon, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Shape Matters: Understanding the Implicit Bias of the Noise Covariance.

Jeff Z. HaoChen, Colin Wei, Jason D. Lee, Tengyu Ma

Proceedings of the Conference on Learning Theory, 2021

2020

Meta-learning Transferable Representations with a Single Target Domain.

Hong Liu, Jeff Z. HaoChen, Colin Wei, Tengyu Ma

CoRR, 2020

2019

Random Shuffling Beats SGD after Finite Epochs.

Jeff Z. HaoChen, Suvrit Sra

Proceedings of the 36th International Conference on Machine Learning, 2019