Colin Wei - RankMe

37 papers A* 16A 1Journal 18Unranked 1

Year	Rank	Type	Title / Venue / Authors
2023	A*	`conf`	Max-Margin Works while Large Margin Fails: Generalization without Uniform Convergence. ICLR Margalit Glasgow, Colin Wei, Mary Wootters, Tengyu Ma
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`	Certified Robustness for Deep Equilibrium Models via Interval Bound Propagation. ICLR Colin Wei, J. Zico Kolter
2022	J	`jnl`	Max-Margin Works while Large Margin Fails: Generalization without Uniform Convergence. CoRR Margalit Glasgow, Colin Wei, Mary Wootters, Tengyu Ma
2022	A*	`conf`	Statistically Meaningful Approximation: a Case Study on Approximating Turing Machines with Transformers. NeurIPS Colin Wei, Yining Chen, Tengyu Ma
2022	—	`—`	Theoretical insights on generalization in supervised and self-supervised deep learning. Colin Wei
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	A*	`conf`	Shape Matters: Understanding the Implicit Bias of the Noise Covariance. COLT Jeff Z. HaoChen, Colin Wei, Jason D. Lee, Tengyu Ma
2021	J	`jnl`	Statistically Meaningful Approximation: a Case Study on Approximating Turing Machines with Transformers. CoRR Colin Wei, Yining Chen, Tengyu Ma
2021	A*	`conf`	Theoretical Analysis of Self-Training with Deep Networks on Unlabeled Data. ICLR Colin Wei, Kendrick Shen, Yining Chen, Tengyu Ma
2021	A*	`conf`	Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuning. NeurIPS Colin Wei, Sang Michael Xie, Tengyu Ma
2021	J	`jnl`	Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuning. CoRR Colin Wei, Sang Michael Xie, Tengyu Ma
2020	A*	`conf`	Improved Sample Complexities for Deep Neural Networks and Robust Classification via an All-Layer Margin. ICLR Colin Wei, 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	A*	`conf`	Self-training Avoids Using Spurious Features Under Domain Shift. NeurIPS Yining Chen, Colin Wei, Ananya Kumar, Tengyu Ma
2020	J	`jnl`	Self-training Avoids Using Spurious Features Under Domain Shift. CoRR Yining Chen, Colin Wei, Ananya Kumar, 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
2020	A*	`conf`	The Implicit and Explicit Regularization Effects of Dropout. ICML Colin Wei, Sham M. Kakade, Tengyu Ma
2020	J	`jnl`	The Implicit and Explicit Regularization Effects of Dropout. CoRR Colin Wei, Sham M. Kakade, Tengyu Ma
2020	J	`jnl`	Theoretical Analysis of Self-Training with Deep Networks on Unlabeled Data. CoRR Colin Wei, Kendrick Shen, Yining Chen, Tengyu Ma
2019	A*	`conf`	Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation. NeurIPS Colin Wei, Tengyu Ma
2019	J	`jnl`	Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation. CoRR Colin Wei, Tengyu Ma
2019	J	`jnl`	Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer Margin. CoRR Colin Wei, Tengyu Ma
2019	A*	`conf`	Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss. NeurIPS Kaidi Cao, Colin Wei, Adrien Gaidon, Nikos Aréchiga, Tengyu Ma
2019	J	`jnl`	Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss. CoRR Kaidi Cao, Colin Wei, Adrien Gaidon, Nikos Aréchiga, Tengyu Ma
2019	A*	`conf`	Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel. NeurIPS Colin Wei, Jason D. Lee, Qiang Liu, Tengyu Ma
2019	A*	`conf`	Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks. NeurIPS Yuanzhi Li, Colin Wei, Tengyu Ma
2019	J	`jnl`	Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks. CoRR Yuanzhi Li, Colin Wei, Tengyu Ma
2018	J	`jnl`	On the Margin Theory of Feedforward Neural Networks. CoRR Colin Wei, Jason D. Lee, Qiang Liu, Tengyu Ma
2017	A*	`conf`	General Bounds on Satisfiability Thresholds for Random CSPs via Fourier Analysis. AAAI Colin Wei, Stefano Ermon
2017	J	`jnl`	General Bounds on Satisfiability Thresholds for Random CSPs via Fourier Analysis. CoRR Colin Wei, Stefano Ermon
2017	J	`jnl`	Generic 3D Representation via Pose Estimation and Matching. CoRR Amir R. Zamir, Tilman Wekel, Pulkit Agrawal, Colin Wei, Jitendra Malik, Silvio Savarese
2017	A	`conf`	Markov Chain Truncation for Doubly-Intractable Inference. AISTATS Colin Wei, Iain Murray
2016	—	`conf`	Generic 3D Representation via Pose Estimation and Matching. ECCV (3) Amir R. Zamir, Tilman Wekel, Pulkit Agrawal, Colin Wei, Jitendra Malik, Silvio Savarese
2016	J	`jnl`	Markov Chain Truncation for Doubly-Intractable Inference. CoRR Colin Wei, Iain Murray