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ORCIDSusan A. Murphy
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- affiliation: Harvard University, Cambridge, MA, USA
- affiliation: University of Michigan, Ann Arbor, MI, USA
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2020 – today
- 2024
[j20]Sorawit Saengkyongam, Niklas Pfister, Predrag Klasnja, Susan A. Murphy, Jonas Peters:
Effect-Invariant Mechanisms for Policy Generalization. J. Mach. Learn. Res. 25: 34:1-34:36 (2024)- [j19]Sarah Rathnam, Sonali Parbhoo, Siddharth Swaroop, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez:
Rethinking Discount Regularization: New Interpretations, Unintended Consequences, and Solutions for Regularization in Reinforcement Learning. J. Mach. Learn. Res. 25: 255:1-255:48 (2024) - [j18]Susobhan Ghosh
, Raphael Kim, Prasidh Chhabria, Raaz Dwivedi, Predrag Klasnja, Peng Liao, Kelly W. Zhang, Susan A. Murphy:
Did we personalize? Assessing personalization by an online reinforcement learning algorithm using resampling. Mach. Learn. 113(7): 3961-3997 (2024) - [c29]Yongyi Guo, Ziping Xu, Susan A. Murphy:
Online learning in bandits with predicted context. AISTATS 2024: 2215-2223 - [c28]Kyra Gan, Esmaeil Keyvanshokooh, Xueqing Liu, Susan A. Murphy:
Contextual Bandits with Budgeted Information Reveal. AISTATS 2024: 3970-3978 - [c27]Eura Nofshin, Siddharth Swaroop, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez:
Reinforcement Learning Interventions on Boundedly Rational Human Agents in Frictionful Tasks. AAMAS 2024: 1482-1491 - [c26]Susobhan Ghosh, Yongyi Guo, Pei-Yao Hung, Lara N. Coughlin, Erin Bonar, Inbal Nahum-Shani, Maureen A. Walton, Susan A. Murphy:
ReBandit: Random Effects Based Online RL Algorithm for Reducing Cannabis Use. IJCAI 2024: 7278-7286 - [i44]Eura Nofshin, Siddharth Swaroop, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez:
Reinforcement Learning Interventions on Boundedly Rational Human Agents in Frictionful Tasks. CoRR abs/2401.14923 (2024) - [i43]Xueqing Liu, Kyra Gan, Esmaeil Keyvanshokooh, Susan A. Murphy:
Online Uniform Risk Times Sampling: First Approximation Algorithms, Learning Augmentation with Full Confidence Interval Integration. CoRR abs/2402.01995 (2024) - [i42]Anna L. Trella, Walter Dempsey, Finale Doshi-Velez, Susan A. Murphy:
Non-Stationary Latent Auto-Regressive Bandits. CoRR abs/2402.03110 (2024) - [i41]Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani, Vivek Shetty, Iris Yan, Finale Doshi-Velez, Susan A. Murphy:
Monitoring Fidelity of Online Reinforcement Learning Algorithms in Clinical Trials. CoRR abs/2402.17003 (2024) - [i40]Susobhan Ghosh, Yongyi Guo, Pei-Yao Hung, Lara N. Coughlin, Erin Bonar, Inbal Nahum-Shani, Maureen A. Walton, Susan A. Murphy:
reBandit: Random Effects based Online RL algorithm for Reducing Cannabis Use. CoRR abs/2402.17739 (2024) - [i39]Zana Buçinca, Siddharth Swaroop, Amanda E. Paluch, Susan A. Murphy, Krzysztof Z. Gajos:
Towards Optimizing Human-Centric Objectives in AI-Assisted Decision-Making With Offline Reinforcement Learning. CoRR abs/2403.05911 (2024) - [i38]Ziping Xu, Kelly W. Zhang, Susan A. Murphy:
The Fallacy of Minimizing Local Regret in the Sequential Task Setting. CoRR abs/2403.10946 (2024) - [i37]Anna L. Trella, Kelly W. Zhang, Stephanie M. Carpenter, David Elashoff, Zara M. Greer, Inbal Nahum-Shani, Dennis Ruenger, Vivek Shetty, Susan A. Murphy:
Oralytics Reinforcement Learning Algorithm. CoRR abs/2406.13127 (2024) - [i36]Susobhan Ghosh, Yongyi Guo, Pei-Yao Hung, Lara N. Coughlin, Erin Bonar, Inbal Nahum-Shani, Maureen A. Walton, Susan A. Murphy:
MiWaves Reinforcement Learning Algorithm. CoRR abs/2408.15076 (2024) - [i35]Anna L. Trella, Kelly W. Zhang, Hinal Jajal, Inbal Nahum-Shani, Vivek Shetty, Finale Doshi-Velez, Susan A. Murphy:
A Deployed Online Reinforcement Learning Algorithm In An Oral Health Clinical Trial. CoRR abs/2409.02069 (2024) - [i34]Anna L. Trella, Susobhan Ghosh, Erin Bonar, Lara N. Coughlin, Finale Doshi-Velez, Yongyi Guo, Pei-Yao Hung, Inbal Nahum-Shani, Vivek Shetty, Maureen A. Walton, Iris Yan, Kelly W. Zhang, Susan A. Murphy:
Effective Monitoring of Online Decision-Making Algorithms in Digital Intervention Implementation. CoRR abs/2409.10526 (2024) - 2023
- [j17]Martin Cousineau, Vedat Verter, Susan A. Murphy, Joelle Pineau:
Estimating causal effects with optimization-based methods: A review and empirical comparison. Eur. J. Oper. Res. 304(2): 367-380 (2023) - [j16]Jessica R. Golbus, Kashvi Gupta, Rachel Stevens, V. Swetha Jeganathan, Evan Luff, Jieru Shi, Walter Dempsey, Thomas Boyden, Bhramar Mukherjee, Sarah Kohnstamm, Vlad Taralunga, Vik Kheterpal, Susan A. Murphy, Predrag V. Klasnja, Sachin Kheterpal, Brahmajee K. Nallamothu:
A randomized trial of a mobile health intervention to augment cardiac rehabilitation. npj Digit. Medicine 6 (2023) - [j15]Eura Shin, Predrag Klasnja, Susan A. Murphy, Finale Doshi-Velez:
Online model selection by learning how compositional kernels evolve. Trans. Mach. Learn. Res. 2023 (2023) - [c25]Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani, Vivek Shetty, Finale Doshi-Velez, Susan A. Murphy:
Reward Design for an Online Reinforcement Learning Algorithm Supporting Oral Self-Care. AAAI 2023: 15724-15730 - [c24]Sarah Rathnam, Sonali Parbhoo, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez:
The Unintended Consequences of Discount Regularization: Improving Regularization in Certainty Equivalence Reinforcement Learning. ICML 2023: 28746-28767 - [c23]Karine Karine, Predrag V. Klasnja, Susan A. Murphy, Benjamin M. Marlin:
Assessing the Impact of Context Inference Error and Partial Observability on RL Methods for Just-In-Time Adaptive Interventions. UAI 2023: 1047-1057 - [i33]Susobhan Ghosh, Raphael Kim, Prasidh Chhabria, Raaz Dwivedi, Predrag V. Klasnja, Peng Liao, Kelly W. Zhang, Susan A. Murphy:
Did we personalize? Assessing personalization by an online reinforcement learning algorithm using resampling. CoRR abs/2304.05365 (2023) - [i32]Karine Karine, Predrag V. Klasnja, Susan A. Murphy, Benjamin M. Marlin:
Assessing the Impact of Context Inference Error and Partial Observability on RL Methods for Just-In-Time Adaptive Interventions. CoRR abs/2305.09913 (2023) - [i31]Kyra Gan, Esmaeil Keyvanshokooh, Xueqing Liu, Susan A. Murphy:
Contextual Bandits with Budgeted Information Reveal. CoRR abs/2305.18511 (2023) - [i30]Sorawit Saengkyongam, Niklas Pfister, Predrag V. Klasnja, Susan A. Murphy, Jonas Peters:
Effect-Invariant Mechanisms for Policy Generalization. CoRR abs/2306.10983 (2023) - [i29]Sarah Rathnam, Sonali Parbhoo, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez:
The Unintended Consequences of Discount Regularization: Improving Regularization in Certainty Equivalence Reinforcement Learning. CoRR abs/2306.11208 (2023) - [i28]Yongyi Guo, Susan A. Murphy:
Online learning in bandits with predicted context. CoRR abs/2307.13916 (2023) - [i27]Shuangning Li, Lluis Salvat Niell, Sung Won Choi, Inbal Nahum-Shani, Guy Shani, Susan A. Murphy:
Dyadic Reinforcement Learning. CoRR abs/2308.07843 (2023) - 2022
- [j14]Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani, Vivek Shetty, Finale Doshi-Velez, Susan A. Murphy:
Designing Reinforcement Learning Algorithms for Digital Interventions: Pre-Implementation Guidelines. Algorithms 15(8): 255 (2022) - [c22]Dimitris Bertsimas, Predrag V. Klasnja, Susan A. Murphy, Liangyuan Na:
Data-driven Interpretable Policy Construction for Personalized Mobile Health. ICDH 2022: 13-22 - [i26]Raaz Dwivedi, Susan A. Murphy, Devavrat Shah:
Counterfactual inference for sequential experimental design. CoRR abs/2202.06891 (2022) - [i25]Kelly W. Zhang, Lucas Janson, Susan A. Murphy:
Statistical Inference After Adaptive Sampling in Non-Markovian Environments. CoRR abs/2202.07098 (2022) - [i24]Martin Cousineau, Vedat Verter, Susan A. Murphy, Joelle Pineau:
Estimating causal effects with optimization-based methods: A review and empirical comparison. CoRR abs/2203.00097 (2022) - [i23]Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani, Vivek Shetty, Finale Doshi-Velez, Susan A. Murphy:
Designing Reinforcement Learning Algorithms for Digital Interventions: Pre-implementation Guidelines. CoRR abs/2206.03944 (2022) - [i22]Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani, Vivek Shetty, Finale Doshi-Velez, Susan A. Murphy:
Reward Design For An Online Reinforcement Learning Algorithm Supporting Oral Self-Care. CoRR abs/2208.07406 (2022) - [i21]Raaz Dwivedi, Katherine Tian, Sabina Tomkins, Predrag V. Klasnja, Susan A. Murphy, Devavrat Shah:
Doubly robust nearest neighbors in factor models. CoRR abs/2211.14297 (2022) - [i20]Eura Shin, Siddharth Swaroop, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez:
Modeling Mobile Health Users as Reinforcement Learning Agents. CoRR abs/2212.00863 (2022) - 2021
- [j13]Sabina Tomkins, Peng Liao, Predrag V. Klasnja, Susan A. Murphy:
IntelligentPooling: practical Thompson sampling for mHealth. Mach. Learn. 110(9): 2685-2727 (2021) - [c21]Jiayu Yao, Emma Brunskill, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez:
Power Constrained Bandits. MLHC 2021: 209-259 - [c20]Kelly W. Zhang, Lucas Janson, Susan A. Murphy:
Statistical Inference with M-Estimators on Adaptively Collected Data. NeurIPS 2021: 7460-7471 - [i19]Kelly W. Zhang, Lucas Janson, Susan A. Murphy:
Statistical Inference with M-Estimators on Bandit Data. CoRR abs/2104.14074 (2021) - [i18]Eura Shin, Pedja Klasnja, Susan A. Murphy, Finale Doshi-Velez:
Online structural kernel selection for mobile health. CoRR abs/2107.09949 (2021) - [i17]Sarah Rathnam, Susan A. Murphy, Finale Doshi-Velez:
Comparison and Unification of Three Regularization Methods in Batch Reinforcement Learning. CoRR abs/2109.08134 (2021) - 2020
- [j12]Peng Liao, Kristjan H. Greenewald, Predrag V. Klasnja, Susan A. Murphy:
Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activity. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 4(1): 18:1-18:22 (2020) - [c19]Kelly W. Zhang, Lucas Janson, Susan A. Murphy:
Inference for Batched Bandits. NeurIPS 2020 - [i16]Kelly W. Zhang, Lucas Janson, Susan A. Murphy:
Inference for Batched Bandits. CoRR abs/2002.03217 (2020) - [i15]Sabina Tomkins, Peng Liao, Predrag V. Klasnja, Serena Yeung, Susan A. Murphy:
Rapidly Personalizing Mobile Health Treatment Policies with Limited Data. CoRR abs/2002.09971 (2020) - [i14]Marianne Menictas, Sabina Tomkins, Susan A. Murphy:
Streamlined Empirical Bayes Fitting of Linear Mixed Models in Mobile Health. CoRR abs/2003.12881 (2020) - [i13]Mashfiqui Rabbi, Meredith Philyaw-Kotov, Jinseok Li, Katherine Li, Bess Rothman, Lexa Giragosian, Maya Reyes, Hannah Gadway, Rebecca M. Cunningham, Erin Bonar, Inbal Nahum-Shani, Maureen A. Walton, Susan A. Murphy, Predrag V. Klasnja:
Translating Behavioral Theory into Technological Interventions: Case Study of an mHealth App to Increase Self-reporting of Substance-Use Related Data. CoRR abs/2003.13545 (2020) - [i12]Jiayu Yao, Emma Brunskill, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez:
Power-Constrained Bandits. CoRR abs/2004.06230 (2020) - [i11]Ashley E. Walton, Linda M. Collins, Predrag V. Klasnja, Inbal Nahum-Shani, Mashfiqui Rabbi, Maureen A. Walton, Susan A. Murphy:
The Micro-Randomized Trial for Developing Digital Interventions: Experimental Design Considerations. CoRR abs/2005.05880 (2020) - [i10]Sabina Tomkins, Peng Liao, Predrag V. Klasnja, Susan A. Murphy:
IntelligentPooling: Practical Thompson Sampling for mHealth. CoRR abs/2008.01571 (2020) - [i9]Marianne Menictas, Sabina Tomkins, Susan A. Murphy:
Fast Physical Activity Suggestions: Efficient Hyperparameter Learning in Mobile Health. CoRR abs/2012.11646 (2020)
2010 – 2019
- 2019
- [j11]Mashfiqui Rabbi, Katherine Li, H. Yanna Yan, Kelly Hall, Predrag V. Klasnja, Susan A. Murphy:
ReVibe: A Context-assisted Evening Recall Approach to Improve Self-report Adherence. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 3(4): 149:1-149:27 (2019) - [c18]Tao Zhang, Geoff A. Jarrad, Susan A. Murphy, Niranjan Bidargaddi:
A smartphone-based behavioural activation application using recommender system. UbiComp/ISWC Adjunct 2019: 250-253 - [i8]Peng Liao, Kristjan H. Greenewald, Predrag V. Klasnja, Susan A. Murphy:
Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activity. CoRR abs/1909.03539 (2019) - [i7]Peng Liao, Predrag V. Klasnja, Susan A. Murphy:
Off-Policy Estimation of Long-Term Average Outcomes with Applications to Mobile Health. CoRR abs/1912.13088 (2019) - 2018
- [j10]Peng Liao, Walter Dempsey, Hillol Sarker, Syed Monowar Hossain, Mustafa al'Absi, Predrag V. Klasnja, Susan A. Murphy:
Just-in-Time but Not Too Much: Determining Treatment Timing in Mobile Health. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2(4): 179:1-179:21 (2018) - [i6]Sabina Tomkins, Predrag V. Klasnja, Susan A. Murphy:
Personalizing Intervention Probabilities By Pooling. CoRR abs/1812.00463 (2018) - 2017
- [j9]Santosh Kumar, Gregory D. Abowd, William T. Abraham, Mustafa al'Absi, Duen Horng Chau, Emre Ertin, Deborah Estrin, Deepak Ganesan, Timothy Hnat, Syed Monowar Hossain, Zachary G. Ives, Jacqueline Kerr, Benjamin M. Marlin, Susan A. Murphy, James M. Rehg, Inbal Nahum-Shani, Vivek Shetty, Ida Sim, Bonnie Spring, Mani B. Srivastava, David W. Wetter:
Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K). IEEE Pervasive Comput. 16(2): 18-22 (2017) - [j8]Korkut Bekiroglu, Constantino Lagoa, Susan A. Murphy, Stephanie T. Lanza:
Control Engineering Methods for the Design of Robust Behavioral Treatments. IEEE Trans. Control. Syst. Technol. 25(3): 979-990 (2017) - [c17]Mashfiqui Rabbi, Meredith Philyaw-Kotov, Jinseok Lee, Anthony Mansour, Laura Dent, Xiaolei Wang, Rebecca M. Cunningham, Erin Bonar, Inbal Nahum-Shani, Predrag V. Klasnja, Maureen A. Walton, Susan A. Murphy:
SARA: a mobile app to engage users in health data collection. UbiComp/ISWC Adjunct 2017: 781-789 - [c16]Blake Wagner III, Elaine Liu, Steven D. Shaw, Gleb Iakovlev, Linlu Zhou, Christina N. Harrington, Gregory D. Abowd, Carolyn Yoon, Santosh Kumar, Susan A. Murphy, Bonnie Spring, Inbal Nahum-Shani:
ewrapper: operationalizing engagement strategies in mHealth. UbiComp/ISWC Adjunct 2017: 790-798 - [c15]Walter H. Dempsey, Alexander Moreno, Christy K. Scott, Michael L. Dennis, David H. Gustafson, Susan A. Murphy, James M. Rehg:
iSurvive: An Interpretable, Event-time Prediction Model for mHealth. ICML 2017: 970-979 - [c14]Kristjan H. Greenewald, Ambuj Tewari, Susan A. Murphy, Predrag V. Klasnja:
Action Centered Contextual Bandits. NIPS 2017: 5977-5985 - [p7]Santosh Kumar, James M. Rehg, Susan A. Murphy:
Introduction to Part I: mHealth Applications and Tools. Mobile Health - Sensors, Analytic Methods, and Applications 2017: 3-6 - [p6]Shawna N. Smith, Andy Jinseok Lee, Kelly Hall, Nicholas J. Seewald, Audrey Boruvka, Susan A. Murphy, Predrag V. Klasnja:
Design Lessons from a Micro-Randomized Pilot Study in Mobile Health. Mobile Health - Sensors, Analytic Methods, and Applications 2017: 59-82 - [p5]Santosh Kumar, James M. Rehg, Susan A. Murphy:
Introduction to Part II: Sensors to mHealth Markers. Mobile Health - Sensors, Analytic Methods, and Applications 2017: 147-150 - [p4]James M. Rehg, Susan A. Murphy, Santosh Kumar:
Introduction to Part III: Markers to mHealth Predictors. Mobile Health - Sensors, Analytic Methods, and Applications 2017: 345-348 - [p3]Hillol Sarker, Karen Hovsepian, Soujanya Chatterjee, Inbal Nahum-Shani, Susan A. Murphy, Bonnie Spring, Emre Ertin, Mustafa al'Absi, Motohiro Nakajima, Santosh Kumar:
From Markers to Interventions: The Case of Just-in-Time Stress Intervention. Mobile Health - Sensors, Analytic Methods, and Applications 2017: 411-433 - [p2]Susan A. Murphy, James M. Rehg, Santosh Kumar:
Introduction to Part IV: Predictors to mHealth Interventions. Mobile Health - Sensors, Analytic Methods, and Applications 2017: 437-441 - [p1]Ambuj Tewari, Susan A. Murphy:
From Ads to Interventions: Contextual Bandits in Mobile Health. Mobile Health - Sensors, Analytic Methods, and Applications 2017: 495-517 - [e1]James M. Rehg, Susan A. Murphy, Santosh Kumar:
Mobile Health - Sensors, Analytic Methods, and Applications. Springer 2017, ISBN 978-3-319-51393-5 [contents] - [i5]Huitian Lei, Ambuj Tewari, Susan A. Murphy:
An Actor-Critic Contextual Bandit Algorithm for Personalized Mobile Health Interventions. CoRR abs/1706.09090 (2017) - [i4]Niko Beerenwinkel, Holger Fröhlich, Susan A. Murphy:
Addressing the Computational Challenges of Personalized Medicine (Dagstuhl Seminar 17472). Dagstuhl Reports 7(11): 130-141 (2017) - 2016
- [i3]Susan A. Murphy, Yanzhen Deng, Eric B. Laber, Hamid Reza Maei, Richard S. Sutton, Katie Witkiewitz:
A Batch, Off-Policy, Actor-Critic Algorithm for Optimizing the Average Reward. CoRR abs/1607.05047 (2016) - 2015
- [j7]Santosh Kumar, Gregory D. Abowd, William T. Abraham, Mustafa al'Absi, J. Gayle Beck, Duen Horng Chau, Tyson Condie, David E. Conroy, Emre Ertin, Deborah Estrin, Deepak Ganesan, Cho Lam, Benjamin M. Marlin, Clay B. Marsh, Susan A. Murphy, Inbal Nahum-Shani, Kevin Patrick, James M. Rehg, Moushumi Sharmin, Vivek Shetty, Ida Sim, Bonnie Spring, Mani B. Srivastava, David W. Wetter:
Center of excellence for mobile sensor data-to-knowledge (MD2K). J. Am. Medical Informatics Assoc. 22(6): 1137-1142 (2015) - 2014
- [c13]Kun Deng, Russ Greiner, Susan A. Murphy:
Budgeted Learning for Developing Personalized Treatment. ICMLA 2014: 7-14 - 2013
- [j6]Raphael Fonteneau, Susan A. Murphy, Louis Wehenkel, Damien Ernst:
Batch mode reinforcement learning based on the synthesis of artificial trajectories. Ann. Oper. Res. 208(1): 383-416 (2013) - [j5]Raphael Fonteneau, Susan A. Murphy, Louis Wehenkel, Damien Ernst:
Stratégies d'échantillonnage pour l'apprentissage par renforcement batch. Rev. d'Intelligence Artif. 27(2): 171-194 (2013) - [c12]Daniel J. Lizotte, Michael Bowling, Susan A. Murphy:
Linear Fitted-Q Iteration with Multiple Reward Functions. ICAPS 2013 - [c11]Korkut Bekiroglu, Constantino M. Lagoa, Susan A. Murphy, Stephanie T. Lanza:
A robust MPC approach to the design of behavioural treatments. CDC 2013: 3505-3510 - 2012
- [j4]Daniel J. Lizotte, Michael Bowling, Susan A. Murphy:
Linear fitted-Q iteration with multiple reward functions. J. Mach. Learn. Res. 13: 3253-3295 (2012) - [i2]Kun Deng, Joelle Pineau, Susan A. Murphy:
Active Learning for Developing Personalized Treatment. CoRR abs/1202.3714 (2012) - [i1]Eric B. Laber, Susan A. Murphy:
Small Sample Inference for Generalization Error in Classification Using the CUD Bound. CoRR abs/1206.3274 (2012) - 2011
- [j3]Susan M. Shortreed, Eric B. Laber, Daniel J. Lizotte, T. Scott Stroup, Joelle Pineau, Susan A. Murphy:
Informing sequential clinical decision-making through reinforcement learning: an empirical study. Mach. Learn. 84(1-2): 109-136 (2011) - [j2]Raphael Fonteneau, Susan A. Murphy, Louis Wehenkel, Damien Ernst:
Estimation Monte Carlo sans modèle de politiques de décision. Rev. d'Intelligence Artif. 25(3): 321-343 (2011) - [c10]Kun Deng, Joelle Pineau, Susan A. Murphy:
Active learning for personalizing treatment. ADPRL 2011: 32-39 - [c9]Raphael Fonteneau, Susan A. Murphy, Louis Wehenkel, Damien Ernst:
Active exploration by searching for experiments that falsify the computed control policy. ADPRL 2011: 40-47 - [c8]Kun Deng, Joelle Pineau, Susan A. Murphy:
Active Learning for Developing Personalized Treatment. UAI 2011: 161-168 - 2010
- [c7]Raphael Fonteneau, Susan A. Murphy, Louis Wehenkel, Damien Ernst:
Towards Min Max Generalization in Reinforcement Learning. ICAART (Revised Selected Papers) 2010: 61-77 - [c6]Raphael Fonteneau, Susan A. Murphy, Louis Wehenkel, Damien Ernst:
A Cautious Approach to Generalization in Reinforcement Learning. ICAART (1) 2010: 64-73 - [c5]Daniel J. Lizotte, Michael H. Bowling, Susan A. Murphy:
Efficient Reinforcement Learning with Multiple Reward Functions for Randomized Controlled Trial Analysis. ICML 2010: 695-702 - [c4]Raphael Fonteneau, Susan A. Murphy, Louis Wehenkel, Damien Ernst:
Model-Free Monte Carlo-like Policy Evaluation. AISTATS 2010: 217-224
2000 – 2009
- 2009
- [c3]Raphaël Fonteneau, Susan A. Murphy, Louis Wehenkel, Damien Ernst:
Inferring bounds on the performance of a control policy from a sample of trajectories. ADPRL 2009: 117-123 - 2008
- [c2]Eric B. Laber, Susan A. Murphy:
Small Sample Inference for Generalization Error in Classification Using the CUD Bound. UAI 2008: 357-365 - 2007
- [c1]Lacey Gunter, Ji Zhu, Susan A. Murphy:
Variable Selection for Optimal Decision Making. AIME 2007: 149-154 - 2005
- [j1]Susan A. Murphy:
A Generalization Error for Q-Learning. J. Mach. Learn. Res. 6: 1073-1097 (2005)
Coauthor Index
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