Yongtao Wu (2022)

Internship project topic: Inductive bias of Transformer

Research Interests

  • Deep learning
  • Over-parametrized models

Biography

Yongtao Wu received a Bachelor’s degree inTelecommunication Engineering from Sun Yat-sen University in 2020, and a Master’s degree in Machine Learning from KTH Royal Institute of Technology in 2022. From July to September 2022 he was an intern at LIONS. In September 2022 he started his PhD at LIONS.

 

 

Robust NAS under adversarial training: benchmark, theory, and beyond

Y. Wu; F. Liu; C-J. Simon-Gabriel; G. Chrysos; V. Cevher 

2024. 12th International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 7-11, 2024.

Revisiting Character-level Adversarial Attacks for Language Models

E. Abad Rocamora; Y. Wu; F. Liu; G. Chrysos; V. Cevher 

2024. 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria, July 21-27, 2024.

On the Convergence of Encoder-only Shallow Transformers

Y. Wu; F. Liu; G. Chrysos; V. Cevher 

2023. 37th Annual Conference on Neural Information Processing Systems, New Orleans, USA, December 10-16. 2023.

Extrapolation and Spectral Bias of Neural Nets with Hadamard Product: a Polynomial Net Study

Y. Wu; Z. Zhu; F. Liu; G. Chrysos; V. Cevher 

2022. 36th Conference on Neural Information Processing Systems (NeurIPS), New Orleans, USA, November 28 – December 3, 2022.