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Jeff Z. HaoChen
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- affiliation: Stanford University, CA, USA
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2020 – today
- 2023
- [c10]Yuhui Zhang, Michihiro Yasunaga, Zhengping Zhou, Jeff Z. HaoChen, James Zou, Percy Liang, Serena Yeung:
Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models. ACL (Findings) 2023: 7479-7498 - [c9]Jeff Z. HaoChen, Tengyu Ma:
A theoretical study of inductive biases in contrastive learning. ICLR 2023 - [c8]Yuhui Zhang, Jeff Z. HaoChen, Shih-Cheng Huang, Kuan-Chieh Wang, James Zou, Serena Yeung:
Diagnosing and Rectifying Vision Models using Language. ICLR 2023 - [i11]Yuhui Zhang, Jeff Z. HaoChen, Shih-Cheng Huang, Kuan-Chieh Wang, James Zou, Serena Yeung:
Diagnosing and Rectifying Vision Models using Language. CoRR abs/2302.04269 (2023) - [i10]Yuhui Zhang, Michihiro Yasunaga, Zhengping Zhou, Jeff Z. HaoChen, James Zou, Percy Liang, Serena Yeung:
Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models. CoRR abs/2305.17311 (2023) - [i9]Arvind V. Mahankali, Jeff Z. HaoChen, Kefan Dong, Margalit Glasgow, Tengyu Ma:
Beyond NTK with Vanilla Gradient Descent: A Mean-Field Analysis of Neural Networks with Polynomial Width, Samples, and Time. CoRR abs/2306.16361 (2023) - 2022
- [c7]Hong Liu, Jeff Z. HaoChen, Adrien Gaidon, Tengyu Ma:
Self-supervised Learning is More Robust to Dataset Imbalance. ICLR 2022 - [c6]Kendrick Shen, Robbie M. Jones, Ananya Kumar, Sang Michael Xie, Jeff Z. HaoChen, Tengyu Ma, Percy Liang:
Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation. ICML 2022: 19847-19878 - [c5]Juhan Bae, Paul Vicol, Jeff Z. HaoChen, Roger B. Grosse:
Amortized Proximal Optimization. NeurIPS 2022 - [c4]Jeff Z. HaoChen, Colin Wei, Ananya Kumar, Tengyu Ma:
Beyond Separability: Analyzing the Linear Transferability of Contrastive Representations to Related Subpopulations. NeurIPS 2022 - [i8]Juhan Bae, Paul Vicol, Jeff Z. HaoChen, Roger B. Grosse:
Amortized Proximal Optimization. CoRR abs/2203.00089 (2022) - [i7]Kendrick Shen, Robbie Jones, Ananya Kumar, Sang Michael Xie, Jeff Z. HaoChen, Tengyu Ma, Percy Liang:
Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation. CoRR abs/2204.00570 (2022) - [i6]Jeff Z. HaoChen, Colin Wei, Ananya Kumar, Tengyu Ma:
Beyond Separability: Analyzing the Linear Transferability of Contrastive Representations to Related Subpopulations. CoRR abs/2204.02683 (2022) - [i5]Jeff Z. HaoChen, Tengyu Ma:
A Theoretical Study of Inductive Biases in Contrastive Learning. CoRR abs/2211.14699 (2022) - 2021
- [c3]Jeff Z. HaoChen, Colin Wei, Jason D. Lee, Tengyu Ma:
Shape Matters: Understanding the Implicit Bias of the Noise Covariance. COLT 2021: 2315-2357 - [c2]Jeff Z. HaoChen, Colin Wei, Adrien Gaidon, Tengyu Ma:
Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss. NeurIPS 2021: 5000-5011 - [i4]Jeff Z. HaoChen, Colin Wei, Adrien Gaidon, Tengyu Ma:
Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss. CoRR abs/2106.04156 (2021) - [i3]Hong Liu, Jeff Z. HaoChen, Adrien Gaidon, Tengyu Ma:
Self-supervised Learning is More Robust to Dataset Imbalance. CoRR abs/2110.05025 (2021) - 2020
- [i2]Jeff Z. HaoChen, Colin Wei, Jason D. Lee, Tengyu Ma:
Shape Matters: Understanding the Implicit Bias of the Noise Covariance. CoRR abs/2006.08680 (2020) - [i1]Hong Liu, Jeff Z. HaoChen, Colin Wei, Tengyu Ma:
Meta-learning Transferable Representations with a Single Target Domain. CoRR abs/2011.01418 (2020)
2010 – 2019
- 2019
- [c1]Jeff Z. HaoChen, Suvrit Sra:
Random Shuffling Beats SGD after Finite Epochs. ICML 2019: 2624-2633
Coauthor Index
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