LE, Lei (乐 磊)

About Me


Research and Publications

Contact Info



I am a PhD candidate in Computer Science, School of Informatics, Computing and Engineering, Indiana University Bloomington. My research interests lie in statistical machine learning, optimization and reinforcement learning. I am now working with Dr. Martha White, mainly on representation learning with regularized Dictionary Learning.

Far better an approximate answer to the right question, which is often vague, than an exact answer to the wrong question, which can always be made precise. --John W. Tukey, The future of data analysis.

Diversity is essential to happiness. --Bertrand Russell, A History of Western Philosophy.

All cowardice comes from not loving or not loving well, which is the same thing. --Woody Allen, Midnight in Paris.

Learning something while forgetting all of them in the future is totally different from not to learn them at all. -- A teacher during my high school.

  • Vincent Liu, Raksha Kumaraswam, Lei Le, and Martha White. The utility of sparse representations for control in reinforcement learning. (Accepted by AAAI 2019).
  • Lei Le, Andrew Patterson, and Martha White. Supervised autoencoders: Improving generalization performance with unsupervised regularizers. Advances in Neural Information Processing Systems(NeurIPS, the former NIPS), pages 107-117, 2018. [PDF]
  • Lei Le and Martha White. Identifying global optimality for dictionary learning. [PDF]
  • Lei Le, Raksha Kumaraswamy, and Martha White. Learning sparse representations in reinforcement learning with sparse coding. In Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI-17, pages 2067–2073, 2017. [PDF]
  • Lei Le and Martha White. Global optimization of regularized factor models using alternating minimization. In 33rd International Conference on Machine Learning (ICML 2016), Advances in Non-convex Analysis and Optimization Workshop , New York City, NY, June 2016.
  • Lei Le, Emilio Ferrara, and Alessandro Flammini. On predictability of rare events leveraging social media: A machine learning perspective. In Proceedings of the 3rd ACM Conference on Online Social Networks (COSN’15), Palo Alto, CA, November 2015. [PDF]

Office: Cubicle 3061W, Luddy Hall
700 N Woodlawn Ave, Bloomington, IN 47408, United States
Email: leile %A%T iu %D%O%T edu

Last Updated in Feb, 2019. [Download]

I love soccer, basketball and baseball. In my spare time, I watch games and play them. I also like playing the guitar, video games, and reading books and manga.