HaoChen, Jeff Z.

11 publications

ICLR 2023 A Theoretical Study of Inductive Biases in Contrastive Learning Jeff Z. HaoChen, Tengyu Ma

ICLR 2023 Diagnosing and Rectifying Vision Models Using Language Yuhui Zhang, Jeff Z. HaoChen, Shih-Cheng Huang, Kuan-Chieh Wang, James Zou, Serena Yeung

NeurIPS 2022 Amortized Proximal Optimization Juhan Bae, Paul Vicol, Jeff Z. HaoChen, Roger B Grosse

NeurIPS 2022 Beyond Separability: Analyzing the Linear Transferability of Contrastive Representations to Related Subpopulations Jeff Z. HaoChen, Colin Wei, Ananya Kumar, Tengyu Ma

ICML 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

NeurIPSW 2022 DrML: Diagnosing and Rectifying Vision Models Using Language Yuhui Zhang, Jeff Z. HaoChen, Shih-Cheng Huang, Kuan-Chieh Wang, James Zou, Serena Yeung

NeurIPSW 2022 DrML: Diagnosing and Rectifying Vision Models Using Language Yuhui Zhang, Jeff Z. HaoChen, Shih-Cheng Huang, Kuan-Chieh Wang, James Zou, Serena Yeung

ICLR 2022 Self-Supervised Learning Is More Robust to Dataset Imbalance Hong Liu, Jeff Z. HaoChen, Adrien Gaidon, Tengyu Ma

NeurIPS 2021 Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss Jeff Z. HaoChen, Colin Wei, Adrien Gaidon, Tengyu Ma

NeurIPSW 2021 Self-Supervised Learning Is More Robust to Dataset Imbalance Hong Liu, Jeff Z. HaoChen, Adrien Gaidon, Tengyu Ma

COLT 2021 Shape Matters: Understanding the Implicit Bias of the Noise Covariance Jeff Z. HaoChen, Colin Wei, Jason Lee, Tengyu Ma