Jeff Z. HaoChen

21 papers A* 9Journal 11Unranked 1

Year	Rank	Type	Title / Venue / Authors
2023	A*	`conf`	A theoretical study of inductive biases in contrastive learning. ICLR Jeff Z. HaoChen, Tengyu Ma
2023	J	`jnl`	Beyond NTK with Vanilla Gradient Descent: A Mean-Field Analysis of Neural Networks with Polynomial Width, Samples, and Time. CoRR Arvind V. Mahankali, Jeff Z. HaoChen, Kefan Dong, Margalit Glasgow, Tengyu Ma
2023	—	`conf`	Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models. ACL (Findings) Yuhui Zhang, Michihiro Yasunaga, Zhengping Zhou, Jeff Z. HaoChen, James Zou, Percy Liang, Serena Yeung
2023	J	`jnl`	Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models. CoRR Yuhui Zhang, Michihiro Yasunaga, Zhengping Zhou, Jeff Z. HaoChen, James Zou, Percy Liang, Serena Yeung
2023	A*	`conf`	Diagnosing and Rectifying Vision Models using Language. ICLR Yuhui Zhang, Jeff Z. HaoChen, Shih-Cheng Huang, Kuan-Chieh Wang, James Zou, Serena Yeung
2023	J	`jnl`	Diagnosing and Rectifying Vision Models using Language. CoRR Yuhui Zhang, Jeff Z. HaoChen, Shih-Cheng Huang, Kuan-Chieh Wang, James Zou, Serena Yeung
2022	J	`jnl`	A Theoretical Study of Inductive Biases in Contrastive Learning. CoRR Jeff Z. HaoChen, Tengyu Ma
2022	A*	`conf`	Amortized Proximal Optimization. NeurIPS Juhan Bae, Paul Vicol, Jeff Z. HaoChen, Roger B. Grosse
2022	J	`jnl`	Amortized Proximal Optimization. CoRR Juhan Bae, Paul Vicol, Jeff Z. HaoChen, Roger B. Grosse
2022	A*	`conf`	Beyond Separability: Analyzing the Linear Transferability of Contrastive Representations to Related Subpopulations. NeurIPS Jeff Z. HaoChen, Colin Wei, Ananya Kumar, Tengyu Ma
2022	J	`jnl`	Beyond Separability: Analyzing the Linear Transferability of Contrastive Representations to Related Subpopulations. CoRR Jeff Z. HaoChen, Colin Wei, Ananya Kumar, Tengyu Ma
2022	A*	`conf`	Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation. ICML Kendrick Shen, Robbie M. Jones, Ananya Kumar, Sang Michael Xie, Jeff Z. HaoChen, Tengyu Ma, Percy Liang
2022	J	`jnl`	Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation. CoRR Kendrick Shen, Robbie Jones, Ananya Kumar, Sang Michael Xie, Jeff Z. HaoChen, Tengyu Ma, Percy Liang
2022	A*	`conf`	Self-supervised Learning is More Robust to Dataset Imbalance. ICLR Hong Liu, Jeff Z. HaoChen, Adrien Gaidon, Tengyu Ma
2021	A*	`conf`	Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss. NeurIPS Jeff Z. HaoChen, Colin Wei, Adrien Gaidon, Tengyu Ma
2021	J	`jnl`	Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss. CoRR Jeff Z. HaoChen, Colin Wei, Adrien Gaidon, Tengyu Ma
2021	J	`jnl`	Self-supervised Learning is More Robust to Dataset Imbalance. CoRR Hong Liu, Jeff Z. HaoChen, Adrien Gaidon, Tengyu Ma
2021	A*	`conf`	Shape Matters: Understanding the Implicit Bias of the Noise Covariance. COLT Jeff Z. HaoChen, Colin Wei, Jason D. Lee, Tengyu Ma
2020	J	`jnl`	Meta-learning Transferable Representations with a Single Target Domain. CoRR Hong Liu, Jeff Z. HaoChen, Colin Wei, Tengyu Ma
2020	J	`jnl`	Shape Matters: Understanding the Implicit Bias of the Noise Covariance. CoRR Jeff Z. HaoChen, Colin Wei, Jason D. Lee, Tengyu Ma
2019	A*	`conf`	Random Shuffling Beats SGD after Finite Epochs. ICML Jeff Z. HaoChen, Suvrit Sra