Jesse Hostetler

According to our database, Jesse Hostetler authored at least 24 papers between 2011 and 2024.

Collaborative distances:

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

2024

AI Evaluation Authorities: A Case Study Mapping Model Audits to Persistent Standards.

Arihant Chadda, Sean McGregor, Jesse Hostetler, Andrea Brennen

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

A domain-agnostic approach for characterization of lifelong learning systems.

Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Eseoghene Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Reddy Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Konidaris, Dhireesha Kudithipudi, Erik G. Learned-Miller, Seungwon Lee, Michael Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine D. Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha

Neural Networks, March, 2023

Data-Centric Governance.

Sean McGregor, Jesse Hostetler

CoRR, 2023

Outcome-Guided Counterfactuals from a Jointly Trained Generative Latent Space.

Eric Yeh, Pedro Sequeira, Jesse Hostetler, Melinda T. Gervasio

Proceedings of the Explainable Artificial Intelligence, 2023

2022

Dynamically throttleable neural networks.

Hengyue Liu, Samyak Parajuli, Jesse Hostetler, Sek M. Chai, Bir Bhanu

Mach. Vis. Appl., 2022

Global and Local Analysis of Interestingness for Competency-Aware Deep Reinforcement Learning.

Pedro Sequeira, Jesse Hostetler, Melinda T. Gervasio

CoRR, 2022

A Framework for Understanding and Visualizing Strategies of RL Agents.

Pedro Sequeira, Daniel Elenius, Jesse Hostetler, Melinda T. Gervasio

CoRR, 2022

Model-Free Generative Replay for Lifelong Reinforcement Learning: Application to Starcraft-2.

Zachary Daniels, Aswin Raghavan, Jesse Hostetler, Abrar Rahman, Indranil Sur, Michael R. Piacentino, Ajay Divakaran

CoRR, 2022

Outcome-Guided Counterfactuals for Reinforcement Learning Agents from a Jointly Trained Generative Latent Space.

Eric Yeh, Pedro Sequeira, Jesse Hostetler, Melinda T. Gervasio

CoRR, 2022

Conformal Prediction Intervals for Markov Decision Process Trajectories.

Thomas G. Dietterich, Jesse Hostetler

CoRR, 2022

Model-Free Generative Replay for Lifelong Reinforcement Learning: Application to Starcraft-2.

Zachary Alan Daniels, Aswin Raghavan, Jesse Hostetler, Abrar Rahman, Indranil Sur, Michael R. Piacentino, Ajay Divakaran, Roberto Corizzo, Kamil Faber, Nathalie Japkowicz, Michael Baron, James Seale Smith, Sahana Pramod Joshi, Zsolt Kira, Cameron Ethan Taylor, Mustafa Burak Gurbuz, Constantine Dovrolis, Tyler L. Hayes, Christopher Kanan, Jhair Gallardo

Proceedings of the Conference on Lifelong Learning Agents, 2022

System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games.

Indranil Sur, Zachary Daniels, Abrar Rahman, Kamil Faber, Gianmarco J. Gallardo, Tyler L. Hayes, Cameron E. Taylor, Mustafa Burak Gurbuz, James Seale Smith, Sahana Pramod Joshi, Nathalie Japkowicz, Michael Baron, Zsolt Kira, Christopher Kanan, Roberto Corizzo, Ajay Divakaran, Michael R. Piacentino, Jesse Hostetler, Aswin Raghavan

Proceedings of the Second International Conference on AI-ML Systems, 2022

2020

Dynamically Throttleable Neural Networks (TNN).

Hengyue Liu, Samyak Parajuli, Jesse Hostetler, Sek M. Chai, Bir Bhanu

CoRR, 2020

Lifelong Learning using Eigentasks: Task Separation, Skill Acquisition, and Selective Transfer.

Aswin Raghavan, Jesse Hostetler, Indranil Sur, Abrar Rahman, Ajay Divakaran

CoRR, 2020

2019

Toward Runtime-Throttleable Neural Networks.

Jesse Hostetler

CoRR, 2019

Generative Memory for Lifelong Reinforcement Learning.

Aswin Raghavan, Jesse Hostetler, Sek M. Chai

CoRR, 2019

Bootstrapping Deep Neural Networks from Approximate Image Processing Pipelines.

Sek M. Chai, Kilho Son, Jesse Hostetler

Proceedings of the 2nd Workshop on Energy Efficient Machine Learning and Cognitive Computing for Embedded Applications, 2019

2018

Bootstrapping Deep Neural Networks from Image Processing and Computer Vision Pipelines.

Kilho Son, Jesse Hostetler, Sek M. Chai

CoRR, 2018

2017

Sample-Based Tree Search with Fixed and Adaptive State Abstractions.

Jesse Hostetler, Alan Fern, Thomas G. Dietterich

J. Artif. Intell. Res., 2017

2015

Progressive Abstraction Refinement for Sparse Sampling.

Jesse Hostetler, Alan Fern, Thomas G. Dietterich

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

2014

State Aggregation in Monte Carlo Tree Search.

Jesse Hostetler, Alan Fern, Tom Dietterich

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013

On Adversarial Policy Switching with Experiments in Real-Time Strategy Games.

Brian King, Alan Fern, Jesse Hostetler

Proceedings of the Twenty-Third International Conference on Automated Planning and Scheduling, 2013

2012

Inferring Strategies from Limited Reconnaissance in Real-time Strategy Games.

Jesse Hostetler, Ethan W. Dereszynski, Thomas G. Dietterich, Alan Fern

Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

2011

Learning Probabilistic Behavior Models in Real-Time Strategy Games.

Ethan W. Dereszynski, Jesse Hostetler, Alan Fern, Thomas G. Dietterich, Thao-Trang Hoang, Mark Udarbe

Proceedings of the Seventh AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2011