I am a PhD student in the Machine Learning department at Carnegie Mellon University, where I work with Ameet Talwalkar. My current research focuses on automating machine learning model selection; the goal is to develop tools and algorithms that will make the practice of machine learning easier and more accessible.
- automated machine learning
- hyperparameter optimization
- active learning
- gaussian processes
- deep learning
- Hyperband: Bandit-Based Configuration Evaluation for Hyperparameter Optimization. L. Li, K. Jamieson, G. DeSalvo, A. Rostamizadeh, A. Talwalkar. ICLR, 2017. [PDF]
- Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization. L. Li, K. Jamieson, G. DeSalvo, A. Rostamizadeh, A. Talwalkar. Journal of Machine Learning Research 18 (2018) 1-52. [PDF, Blog1, Blog2]
- Massively Parallel Hyperparameter Tuning. L. Li, K. Jamieson, A. Rostamizadeh, K. Gonina, M. Hardt, B. Recht, A. Talwalkar. In submission.
- Pipeline-Aware Hyperparameter Optimization. L. Li, E. Sparks, R. Zhang, K. Jamieson, A. Talwalkar. In submission.
- June 2018: Hyperband published in JMLR
- February 2018: Poster at SysML
- January 2018: Transferred to CMU
- October 2017: Poster at SCMLS
- Parallelizing Hyperband for Large-Scale Tuning
- Summer 2017: Intern at Google Research
- Worked with Afshin Rostamizadeh and Jean-François Kagy on active learning.
- April 2017: Poster at ICLR
- Hyperband: Bandit-Based Configuration Evaluation for Hyperparameter Optimization
- Student Volunteer
- Awarded Travel Grant