Colin Wei

According to our database, Colin Wei authored at least 22 papers between 2016 and 2023.

Collaborative distances:

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

2023

Max-Margin Works while Large Margin Fails: Generalization without Uniform Convergence.

Margalit Glasgow, Colin Wei, Mary Wootters, Tengyu Ma

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Theoretical insights on generalization in supervised and self-supervised deep learning.

Colin Wei

PhD thesis, 2022

Statistically Meaningful Approximation: a Case Study on Approximating Turing Machines with Transformers.

Colin Wei, Yining Chen, Tengyu Ma

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

Certified Robustness for Deep Equilibrium Models via Interval Bound Propagation.

Colin Wei, J. Zico Kolter

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuning.

Colin Wei, Sang Michael Xie, Tengyu Ma

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

Theoretical Analysis of Self-Training with Deep Networks on Unlabeled Data.

Colin Wei, Kendrick Shen, Yining Chen, Tengyu Ma

Proceedings of the 9th International Conference on Learning Representations, 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

Self-training Avoids Using Spurious Features Under Domain Shift.

Yining Chen, Colin Wei, Ananya Kumar, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

The Implicit and Explicit Regularization Effects of Dropout.

Colin Wei, Sham M. Kakade, Tengyu Ma

Proceedings of the 37th International Conference on Machine Learning, 2020

Improved Sample Complexities for Deep Neural Networks and Robust Classification via an All-Layer Margin.

Colin Wei, Tengyu Ma

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer Margin.

Colin Wei, Tengyu Ma

CoRR, 2019

Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation.

Colin Wei, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel.

Colin Wei, Jason D. Lee, Qiang Liu, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks.

Yuanzhi Li, Colin Wei, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss.

Kaidi Cao, Colin Wei, Adrien Gaidon, Nikos Aréchiga, Tengyu Ma

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

On the Margin Theory of Feedforward Neural Networks.

Colin Wei, Jason D. Lee, Qiang Liu, Tengyu Ma

CoRR, 2018

2017

Markov Chain Truncation for Doubly-Intractable Inference.

Colin Wei, Iain Murray

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

General Bounds on Satisfiability Thresholds for Random CSPs via Fourier Analysis.

Colin Wei, Stefano Ermon

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Generic 3D Representation via Pose Estimation and Matching.

Amir R. Zamir, Tilman Wekel, Pulkit Agrawal, Colin Wei, Jitendra Malik, Silvio Savarese

Proceedings of the Computer Vision - ECCV 2016, 2016