I am a doctoral student in the Theoretical and Emprical Data Science Lab supervised by Fei Sha. My reserch topic lies at the intersection of optimization and reinforcement learning.
I did my undergraduate at the University of Southern California, double majoring in Computer Science and Mathematics. My research focused on machine learning, distributed systems, and mathematical optimization.
I also like skiing (a lot).
I just published an official tutorial on the distributed package of PyTorch. Thanks to the community for their help in answering my questions ! [Tutorial]
Together with Prof. Chunming Wang, we submitted a workshop paper presenting our work on second-order optimization for distributed deep learning to ICLR17. Update: It was accepted! [Link]
S. Arnold, E. Chu, F. Valero-Cuevas, 2016, SoCal ML Symposium
Randopt is a python package to streamline the search for good hyper-parameters. It provides a programmatic interface to serialize, choose, and visualize hyper-parameters and results. [GitHub Repo, Blog Post]
Comparing the performance of simulated annealing against a simulation of adiabatic quantum computing on Ising problems. [GitHub Repo]
Simply the best skiing website ever ? [Website]