Online Learning with Randomized Neural Networks

Working Papers

Arielle Anderer, PhD Candidate, The Wharton School; Hamsa Bastani, Operations, Information and Decisions, The Wharton School; Divya Singhvi, NYU Stern Abstract: This project adapts online learning techniques to unstructured data, focusing on neural networks. We posit a non-parametric multi-armed bandit algorithm with context that uses a neural network for itsRead More

Unmasking Sex-Trafficking Supply Chains With Deep Web Data

Funded Research Proposal

High resource constraints and the covert nature of sex trafficking provide significant barriers to developing data-driven innovations that inform law enforcement investigations and trials. We leverage massive deep web data (collected globally from leading adult services websites) in tandem with a novel machine learning framework to unmask sex-trafficking recruitment-to-sales pathways.Read More

Leveraging Data to More Efficiently Predict the Efficacy of Medical Treatments in New Spaces

Funded Research Proposal

This proposal requests research funding for the development of two papers that propose novel methods for leveraging large amounts of imprecise information along with small amounts of specific information to improve the efficacy of medical treatment. Read More