Wei Hu

Affiliations:

Princeton University, Computer Science Department, NJ, USA

According to our database¹, Wei Hu authored at least 22 papers between 2017 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

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In proceedings

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PhD thesis

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Links

On csauthors.net:

Bibliography

2024

Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2021

Understanding Deep Learning via Analyzing Dynamics of Gradient Descent

[BibT_eX]

[DOI]

Wei Hu

PhD thesis, 2021

When is particle filtering efficient for planning in partially observed linear dynamical systems?

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Near-Optimal Linear Regression under Distribution Shift.

[BibT_eX]

[DOI]

Qi Lei

Wei Hu

Jason D. Lee

Proceedings of the 38th International Conference on Machine Learning, 2021

Impact of Representation Learning in Linear Bandits.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

Few-Shot Learning via Learning the Representation, Provably.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Provable Benefits of Representation Learning in Linear Bandits.

[BibT_eX]

[DOI]

CoRR, 2020

When is Particle Filtering Efficient for POMDP Sequential Planning?

[BibT_eX]

[DOI]

CoRR, 2020

Simple and Effective Regularization Methods for Training on Noisily Labeled Data with Generalization Guarantee.

[BibT_eX]

[DOI]

Wei Hu

Zhiyuan Li

Dingli Yu

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

2019

Enhanced Convolutional Neural Tangent Kernels.

[BibT_eX]

[DOI]

CoRR, 2019

Understanding Generalization of Deep Neural Networks Trained with Noisy Labels.

[BibT_eX]

[DOI]

Wei Hu

Zhiyuan Li

Dingli Yu

CoRR, 2019

Explaining Landscape Connectivity of Low-cost Solutions for Multilayer Nets.

[BibT_eX]

[DOI]

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

On Exact Computation with an Infinitely Wide Neural Net.

[BibT_eX]

[DOI]

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

Implicit Regularization in Deep Matrix Factorization.

[BibT_eX]

[DOI]

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

Width Provably Matters in Optimization for Deep Linear Neural Networks.

[BibT_eX]

[DOI]

Simon S. Du

Wei Hu

Proceedings of the 36th International Conference on Machine Learning, 2019

Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

Linear Convergence of the Primal-Dual Gradient Method for Convex-Concave Saddle Point Problems without Strong Convexity.

[BibT_eX]

[DOI]

Simon S. Du

Wei Hu

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Online Improper Learning with an Approximation Oracle.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced.

[BibT_eX]

[DOI]

Simon S. Du

Wei Hu

Jason D. Lee

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

An Analysis of the t-SNE Algorithm for Data Visualization.

[BibT_eX]

[DOI]

Sanjeev Arora

Wei Hu

Pravesh K. Kothari

Proceedings of the Conference On Learning Theory, 2018

2017

Linear Convergence of a Frank-Wolfe Type Algorithm over Trace-Norm Balls.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Wei Hu

Timeline

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