Luke Bornn

According to our database, Luke Bornn authored at least 13 papers between 2013 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

A framework for the fine-grained evaluation of the instantaneous expected value of soccer possessions.

Javier Fernández, Luke Bornn, Daniel Cervone

Mach. Learn., 2021

Inverse Bayesian Optimization: Learning Human Search Strategies in a Sequential Optimization Task.

Nathan Sandholtz, Yohsuke Miyamoto, Luke Bornn, Maurice Smith

CoRR, 2021

2020

SoccerMap: A Deep Learning Architecture for Visually-Interpretable Analysis in Soccer.

Javier Fernández, Luke Bornn

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track, 2020

2018

Time Perception Machine: Temporal Point Processes for the When, Where and What of Activity Prediction.

Yatao Zhong, Bicheng Xu, Guang-Tong Zhou, Luke Bornn, Greg Mori

CoRR, 2018

2017

The use of a single pseudo-sample in approximate Bayesian computation.

Luke Bornn, Natesh S. Pillai, Aaron Smith, Dawn Woodard

Stat. Comput., 2017

Modeling offensive player movement in professional basketball.

Steven Wu, Luke Bornn

PeerJ Prepr., 2017

Improving simulated annealing through derandomization.

Mathieu Gerber, Luke Bornn

J. Glob. Optim., 2017

Adjusting for scorekeeper bias in NBA box scores.

Matthew van Bommel, Luke Bornn

Data Min. Knowl. Discov., 2017

Learning Person Trajectory Representations for Team Activity Analysis.

Nazanin Mehrasa, Yatao Zhong, Frederick Tung, Luke Bornn, Greg Mori

CoRR, 2017

2016

Herded Gibbs Sampling.

Yutian Chen, Luke Bornn, Nando de Freitas, Mareija Eskelin, Jing Fang, Max Welling

J. Mach. Learn. Res., 2016

2014

Diversifying Sparsity Using Variational Determinantal Point Processes.

Nematollah Kayhan Batmanghelich, Gerald T. Quon, Alex Kulesza, Manolis Kellis, Polina Golland, Luke Bornn

CoRR, 2014

Factorized Point Process Intensities: A Spatial Analysis of Professional Basketball.

Andrew C. Miller, Luke Bornn, Ryan P. Adams, Kirk Goldsberry

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Sequential Monte Carlo Bandits.

Michael Cherkassky, Luke Bornn

CoRR, 2013