124 citations · 147 across the 12 of their papers we have counts for
5 papers · 1 filter
Massively Scalable Inverse Reinforcement Learning in Google Maps
Matt Barnes, Matthew Abueg, Oliver F. Lange +5
Inverse reinforcement learning (IRL) offers a powerful and general framework for learning humans' latent preferences in route recommendation, yet no approach has successfully addre…
Neural Nonnegative Matrix Factorization for Hierarchical Multilayer Topic Modeling
Tyler Will, Runyu Zhang, Eli Sadovnik +5
We introduce a new method based on nonnegative matrix factorization, Neural NMF, for detecting latent hierarchical structure in data. Datasets with hierarchical structure arise in…
Analysis of Legal Documents via Non-negative Matrix Factorization Methods
Ryan Budahazy, Lu Cheng, Yihuan Huang +7
The California Innocence Project (CIP), a clinical law school program aiming to free wrongfully convicted prisoners, evaluates thousands of mails containing new requests for assist…
Hierarchical Classification using Binary Data
Denali Molitor, Deanna Needell
In classification problems, especially those that categorize data into a large number of classes, the classes often naturally follow a hierarchical structure. That is, some classes…
Model Agnostic Supervised Local Explanations
Gregory Plumb, Denali Molitor, Ameet Talwalkar
Model interpretability is an increasingly important component of practical machine learning. Some of the most common forms of interpretability systems are example-based, local, and…