Taylor W. Killian

According to our database, Taylor W. Killian authored at least 29 papers between 2013 and 2026.

Collaborative distances:

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

2026

LARK: Learnability-Grounded Trajectory Selection for Efficient Reasoning Distillation.

Tianrun Yu, Kaixiang Zhao, Chih-Chun Chen, Amanda Hughes, Taylor W. Killian, Fenglong Ma, Weitong Zhang, Porter Jenkins

CoRR, May, 2026

Efficient Agentic Reasoning Through Self-Regulated Simulative Planning.

Mingkai Deng, Jinyu Hou, Lara Sá Neves, Varad Pimpalkhute, Taylor W. Killian, Zhengzhong Liu, Eric P. Xing

CoRR, May, 2026

Behavior Cue Reasoning: Monitorable Reasoning Improves Efficiency and Safety through Oversight.

Christopher Zhang Cui, Taylor W. Killian, Prithviraj Ammanabrolu

CoRR, May, 2026

IsoCompute Playbook: Optimally Scaling Sampling Compute for LLM RL.

Zhoujun Cheng, Yutao Xie, Yuxiao Qu, Amrith Setlur, Shibo Hao, Varad Pimpalkhute, Tongtong Liang, Feng Yao, Zhengzhong Liu, Eric P. Xing, Virginia Smith, Ruslan Salakhutdinov, Zhiting Hu, Taylor W. Killian, Aviral Kumar

CoRR, March, 2026

Improving and Accelerating Offline RL in Large Discrete Action Spaces with Structured Policy Initialization.

Matthew Landers, Taylor W. Killian, Thomas Hartvigsen, Afsaneh Doryab

CoRR, January, 2026

2025

Concise Reasoning in the Lens of Lagrangian Optimization.

Chengqian Gao, Haonan Li, Taylor W. Killian, Jianshu She, Renxi Wang, Liqun Ma, Zhoujun Cheng, Shibo Hao, Zhiqiang Xu

CoRR, October, 2025

K2-Think: A Parameter-Efficient Reasoning System.

Zhoujun Cheng, Richard Fan, Shibo Hao, Taylor W. Killian, Haonan Li, Suqi Sun, Hector Ren, Alexander Moreno, Daqian Zhang, Tianjun Zhong, Yuxin Xiong, Yuanzhe Hu, Yutao Xie, Xudong Han, Yuqi Wang, Varad Pimpalkhute, Yonghao Zhuang, Aaryamonvikram Singh, Xuezhi Liang, Anze Xie, Jianshu She, Desai Fan, Chengqian Gao, Liqun Ma, Mikhail Yurochkin, John Maggs, Xuezhe Ma, Guowei He, Zhiting Hu, Zhengzhong Liu, Eric P. Xing

CoRR, September, 2025

Revisiting Reinforcement Learning for LLM Reasoning from A Cross-Domain Perspective.

Zhoujun Cheng, Shibo Hao, Tianyang Liu, Fan Zhou, Yutao Xie, Feng Yao, Yuexin Bian, Yonghao Zhuang, Nilabjo Dey, Yuheng Zha, Yi Gu, Kun Zhou, Yuqi Wang, Yuan Li, Richard Fan, Jianshu She, Chengqian Gao, Abulhair Saparov, Haonan Li, Taylor W. Killian, Mikhail Yurochkin, Zhengzhong Liu, Eric P. Xing, Zhiting Hu

CoRR, June, 2025

SAINT: Attention-Based Modeling of Sub-Action Dependencies in Multi-Action Policies.

Matthew Landers, Taylor W. Killian, Thomas Hartvigsen, Afsaneh Doryab

CoRR, May, 2025

Revisiting Reinforcement Learning for LLM Reasoning from A Cross-Domain Perspective.

Jorge (Zhoujun) Cheng, Shibo Hao, Tianyang Liu, Fan Zhou, Yutao Xie, Feng Yao, Yuexin Bian, Nilabjo Dey, Yonghao Zhuang, Yuheng Zha, Yi Gu, Kun Zhou, Yuqi Wang, Yuan Li, Richard Fan, Jianshu She, Chengqian Gao, Abulhair Saparov, Taylor W. Killian, Haonan Li, Mikhail Yurochkin, Eric P. Xing, Zhengzhong Liu, Zhiting Hu

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Robust Autonomy Emerges from Self-Play.

Marco Francis Cusumano-Towner, David Hafner, Alexander Hertzberg, Brody Huval, Aleksei Petrenko, Eugene Vinitsky, Erik Wijmans, Taylor W. Killian, Stuart Bowers, Ozan Sener, Philipp Krähenbühl, Vladlen Koltun

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Clinically Motivated Sequential Decision Making Under Uncertainty in Offline Settings

Taylor W. Killian

PhD thesis, 2024

Identifying Differential Patient Care Through Inverse Intent Inference.

Hyewon Jeong, Siddharth Nayak, Taylor W. Killian, Sanjat Kanjilal

CoRR, 2024

Offline Reinforcement Learning With Combinatorial Action Spaces.

Matthew Landers, Taylor W. Killian, Hugo Barnes, Thomas Hartvigsen, Afsaneh Doryab

CoRR, 2024

2023

Risk Sensitive Dead-end Identification in Safety-Critical Offline Reinforcement Learning.

Taylor W. Killian, Sonali Parbhoo, Marzyeh Ghassemi

Trans. Mach. Learn. Res., 2023

Continuous Time Evidential Distributions for Irregular Time Series.

Taylor W. Killian, Haoran Zhang, Thomas Hartvigsen, Ava P. Amini

CoRR, 2023

2022

Machine Learning for Health (ML4H) 2022.

Antonio Parziale, Monica Agrawal, Shengpu Tang, Kristen Severson, Luis Oala, Adarsh Subbaswamy, Sayantan Kumar, Elora D. M. Schörverth, Stefan Hegselmann, Helen Zhou, Ghada Zamzmi, Purity Mugambi, Elena Sizikova, Girmaw Abebe Tadesse, Yuyin Zhou, Taylor W. Killian, Haoran Zhang, Fahad Kamran, Andrea Hobby, Mars Huang, Ahmed M. Alaa, Harvineet Singh, Irene Y. Chen, Shalmali Joshi

Proceedings of the Machine Learning for Health, 2022

Counterfactually Guided Policy Transfer in Clinical Settings.

Taylor W. Killian, Marzyeh Ghassemi, Shalmali Joshi

Proceedings of the Conference on Health, Inference, and Learning, 2022

2021

Medical Dead-ends and Learning to Identify High-Risk States and Treatments.

Mehdi Fatemi, Taylor W. Killian, Jayakumar Subramanian, Marzyeh Ghassemi

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare.

Taylor W. Killian, Haoran Zhang, Jayakumar Subramanian, Mehdi Fatemi, Marzyeh Ghassemi

Proceedings of the Machine Learning for Health Workshop, 2020

Optimization Methods for Interpretable Differentiable Decision Trees Applied to Reinforcement Learning.

Andrew Silva, Matthew C. Gombolay, Taylor W. Killian, Ivan Dario Jimenez Jimenez, Sung-Hyun Son

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Multiple Sclerosis Severity Classification From Clinical Text.

Alister D. Costa, Stefan Denkovski, Michal Malyska, Sae Young Moon, Brandon Rufino, Zhen Yang, Taylor W. Killian, Marzyeh Ghassemi

Proceedings of the 3rd Clinical Natural Language Processing Workshop, 2020

2019

Kernelized Capsule Networks.

Taylor W. Killian, Justin A. Goodwin, Olivia M. Brown, Sung-Hyun Son

CoRR, 2019

Interpretable Reinforcement Learning via Differentiable Decision Trees.

Ivan Dario Jimenez Rodriguez, Taylor W. Killian, Sung-Hyun Son, Matthew C. Gombolay

CoRR, 2019

2018

Learning Robust Representations for Automatic Target Recognition.

Justin A. Goodwin, Olivia M. Brown, Taylor W. Killian, Sung-Hyun Son

CoRR, 2018

2017

Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes.

Taylor W. Killian, Samuel Daulton, Finale Doshi-Velez, George Dimitri Konidaris

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes.

Taylor W. Killian, George Dimitri Konidaris, Finale Doshi-Velez

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Transfer Learning Across Patient Variations with Hidden Parameter Markov Decision Processes.

Taylor W. Killian, George Dimitri Konidaris, Finale Doshi-Velez

CoRR, 2016

2013

Frequency uniqueness in ring oscillator Physical Unclonable Functions on FPGAs.

Muslim Mustapa, Mohammed Y. Niamat, Mansoor Alam, Taylor W. Killian

Proceedings of the IEEE 56th International Midwest Symposium on Circuits and Systems, 2013