Large Scale Generative AI Text Applied to Sports and Music

no code implementations • 31 Jan 2024 • Aaron Baughman, Stephen Hammer, Rahul Agarwal, Gozde Akay, Eduardo Morales, Tony Johnson, Leonid Karlinsky, Rogerio Feris

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.

Study of Feature Importance for Quantum Machine Learning Models

no code implementations • 18 Feb 2022 • Aaron Baughman, Kavitha Yogaraj, Raja Hebbar, Sudeep Ghosh, Rukhsan Ul Haq, Yoshika Chhabra

This work presents the first study of its kind in which feature importance for QML models has been explored and contrasted against their classical machine learning (CML) equivalents.

BIG-bench Machine Learning Feature Importance +1

Deep Artificial Intelligence for Fantasy Football Language Understanding

no code implementations • 4 Nov 2021 • Aaron Baughman, Micah Forester, Jeff Powell, Eduardo Morales, Shaun McPartlin, Daniel Bohm

The use of trained statistical entity detectors and document2vector models applied to over 100, 000 news sources and 2. 3 million articles, videos and podcasts each day enables the system to comprehend natural language with an analogy test accuracy of 100% and keyword test accuracy of 80%.

Large Scale Diverse Combinatorial Optimization: ESPN Fantasy Football Player Trades

no code implementations • 4 Nov 2021 • Aaron Baughman, Daniel Bohm, Micah Forster, Eduardo Morales, Jeff Powell, Shaun McPartlin, Raja Hebbar, Kavitha Yogaraj, Yoshika Chhabra, Sudeep Ghosh, Rukhsan Ul Haq, Arjun Kashyap

Team managers can quickly discover that their team has a low score ceiling even if they start their best active players.

Combinatorial Optimization Fairness +1