5 citations · 5 across the 4 of their papers we have counts for
4 papers
Large Scale Generative AI Text Applied to Sports and Music
Aaron Baughman, Stephen Hammer, Rahul Agarwal +5
We address the problem of scaling up the production of media content, including commentary and personalized news stories, for large-scale sports and music events worldwide. Our app…
Study of Feature Importance for Quantum Machine Learning Models
Aaron Baughman, Kavitha Yogaraj, Raja Hebbar +3
Predictor importance is a crucial part of data preprocessing pipelines in classical and quantum machine learning (QML). This work presents the first study of its kind in which feat…
Deep Artificial Intelligence for Fantasy Football Language Understanding
Aaron Baughman, Micah Forester, Jeff Powell +3
Fantasy sports allow fans to manage a team of their favorite athletes and compete with friends. The fantasy platform aligns the real-world statistical performance of athletes to fa…
Large Scale Diverse Combinatorial Optimization: ESPN Fantasy Football Player Trades
Aaron Baughman, Daniel Bohm, Micah Forster +9
Even skilled fantasy football managers can be disappointed by their mid-season rosters as some players inevitably fall short of draft day expectations. Team managers can quickly di…