I am a PhD student in Carnegie Mellon University's Computer Science Department advised by Nina Balcan and Ameet Talwalkar. My research focuses on foundations and applications of machine learning, most recently meta-learning, unsupervised representation learning, and natural language processing. Previously, I received an AB in Mathematics and an MSE in Computer Science from Princeton University, where I worked with Sanjeev Arora.
Adaptive Gradient-Based Meta-Learning Methods. To Appear in NeurIPS 2019.
Differentially Private Meta-Learning.
Jeffrey Li, Mikhail Khodak, Sebastian Caldas, Ameet Talwalkar.
Provable Guarantees for Gradient-Based Meta-Learning. ICML 2019.
A Theoretical Analysis of Contrastive Unsupervised Representation Learning. ICML 2019.
A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors. ACL 2018.
A Compressed Sensing View of Unsupervised Text Embeddings, Bag-of-n-Grams, and LSTMs. ICLR 2018.