Emma Brunskill

248 papers A* 67A 28B 24C 1Misc 3Journal 100Unranked 24

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Assessing the Quality of AI-Generated Exams: A Large-Scale Field Study. AAAI Calvin Isley, Joshua Gilbert, Evangelos Kassos, Michaela Kocher, Allen Nie, Emma Brunskill, Benjamin W. Domingue, Jake Hofman, Joscha Legewie, Teddy Svoronos, Charlotte Tuminelli, Sharad Goel
2026	A*	`conf`	Bloom: Designing for LLM-Augmented Behavior Change Interactions. CHI Matthew Jörke, Defne Genç, Valentin Teutschbein, Shardul Sapkota, Sarah Chung, Paul Schmiedmayer, Maria Ines Campero, Abby C. King, Emma Brunskill, James A. Landay
2026	A*	`conf`	Can LLM-Simulated Practice and Feedback Upskill Human Counselors? A Randomized Study with 90+ Novice Counselors. CHI Ryan Louie, Raj Sanjay Shah, Ifdita Hasan Orney, Juan Pablo Pacheco, Emma Brunskill, Diyi Yang
2026	J	`jnl`	Learning to Be Fair: A Consequentialist Approach to Equitable Decision Making. Manag. Sci. Alex Chohlas-Wood, Madison Coots, Henry Zhu, Emma Brunskill, Sharad Goel
2025	J	`jnl`	Assessing the Quality of AI-Generated Exams: A Large-Scale Field Study. CoRR Calvin Isley, Joshua Gilbert, Evangelos Kassos, Michaela Kocher, Allen Nie, Emma Brunskill, Benjamin W. Domingue, Jake Hofman, Joscha Legewie, Teddy Svoronos, Charlotte Tuminelli, Sharad Goel
2025	J	`jnl`	Bloom: Designing for LLM-Augmented Behavior Change Interactions. CoRR Matthew Jörke, Defne Genç, Valentin Teutschbein, Shardul Sapkota, Sarah Chung, Paul Schmiedmayer, Maria Ines Campero, Abby C. King, Emma Brunskill, James A. Landay
2025	J	`jnl`	Can LLM-Simulated Practice and Feedback Upskill Human Counselors? A Randomized Study with 90+ Novice Counselors. CoRR Ryan Louie, Ifdita Hasan Orney, Juan Pablo Pacheco, Raj Sanjay Shah, Emma Brunskill, Diyi Yang
2025	A*	`conf`	Cost-Aware Near-Optimal Policy Learning. AAAI Joy He-Yueya, Jonathan Lee, Matthew Jörke, Emma Brunskill
2025	J	`jnl`	Efficient RL for optimizing conversation level outcomes with an LLM-based tutor. CoRR Hyunji Nam, Omer Gottesman, Amy Zhang, Dean P. Foster, Emma Brunskill, Lyle H. Ungar
2025	A	`conf`	Exploring the Benefit of Customizing Feedback Interventions For Educators and Students With Offline Contextual Multi-Armed Bandits. LAK Joy Yun, Allen Nie, Emma Brunskill, Dorottya Demszky
2025	A*	`conf`	GPTCoach: Towards LLM-Based Physical Activity Coaching. CHI Matthew Jörke, Shardul Sapkota, Lyndsea Warkenthien, Niklas Vainio, Paul Schmiedmayer, Emma Brunskill, James A. Landay
2025	—	`conf`	Human Tutoring Improves the Impact of AI Tutor Use on Learning Outcomes. AIED (4) Ashish Gurung, Jionghao Lin, Jordan Gutterman, Danielle R. Thomas, Alex Houk, Shivang Gupta, Emma Brunskill, Lee G. Branstetter, Vincent Aleven, Kenneth R. Koedinger
2025	J	`jnl`	PERRY: Policy Evaluation with Confidence Intervals using Auxiliary Data. CoRR Aishwarya Mandyam, Jason Meng, Ge Gao, Jiankai Sun, Mac Schwager, Barbara E. Engelhardt, Emma Brunskill
2025	A	`conf`	Predicting Long-Term Student Outcomes from Short-Term EdTech Log Data. LAK Ge Gao, Amelia Leon, Andrea Jetten, Jasmine Turner, Husni Almoubayyed, Stephen Fancsali, Emma Brunskill
2025	J	`jnl`	Repairing Reward Functions with Human Feedback to Mitigate Reward Hacking. CoRR Stephane Hatgis-Kessell, Logan Mondal Bhamidipaty, Emma Brunskill
2024	—	`conf`	A Fast and Accurate Machine Learning Autograder for the Breakout Assignment. SIGCSE (1) Evan Zheran Liu, David Yuan, Ahmed Ahmed, Elyse Cornwall, Juliette Woodrow, Kaylee Burns, Allen Nie, Emma Brunskill, Chris Piech, Chelsea Finn
2024	A*	`conf`	Adaptive Instrument Design for Indirect Experiments. ICLR Yash Chandak, Shiv Shankar, Vasilis Syrgkanis, Emma Brunskill
2024	—	`conf`	Adaptive Interventions with User-Defined Goals for Health Behavior Change. CHIL Aishwarya Mandyam, Matthew Jörke, William Denton, Barbara E. Engelhardt, Emma Brunskill
2024	—	`conf`	Brief, Just-in-Time Teaching Tips to Support Computer Science Tutors. SIGCSE (1) Alan Y. Cheng, Ellie Tanimura, Joseph Tey, Andrew C. Wu, Emma Brunskill
2024	J	`jnl`	Data-driven Error Estimation: Upper Bounding Multiple Errors with No Technical Debt. CoRR Sanath Kumar Krishnamurthy, Susan Athey, Emma Brunskill
2024	J	`jnl`	Estimating Optimal Policy Value in Linear Contextual Bandits Beyond Gaussianity. Trans. Mach. Learn. Res. Jonathan Lee, Weihao Kong, Aldo Pacchiano, Vidya Muthukumar, Emma Brunskill
2024	A	`conf`	Estimating the Causal Treatment Effect of Unproductive Persistence. LAK Amelia Leon, Allen Nie, Yash Chandak, Emma Brunskill
2024	B	`conf`	Evaluating and Optimizing Educational Content with Large Language Model Judgments. EDM Joy He-Yueya, Noah D. Goodman, Emma Brunskill
2024	J	`jnl`	Evaluating and Optimizing Educational Content with Large Language Model Judgments. CoRR Joy He-Yueya, Noah D. Goodman, Emma Brunskill
2024	B	`conf`	Examining the Use of an AI-Powered Teacher Orchestration Tool at Scale. L@S Emma Brunskill, Kole A. Norberg, Stephen Fancsali, Steven Ritter
2024	J	`jnl`	Experiment Planning with Function Approximation. CoRR Aldo Pacchiano, Jonathan N. Lee, Emma Brunskill
2024	A	`conf`	Improving Student Learning with Hybrid Human-AI Tutoring: A Three-Study Quasi-Experimental Investigation. LAK Danielle R. Thomas, Jionghao Lin, Erin Gatz, Ashish Gurung, Shivang Gupta, Kole Norberg, Stephen E. Fancsali, Vincent Aleven, Lee G. Branstetter, Emma Brunskill, Kenneth R. Koedinger
2024	A*	`conf`	Minimax-Regret Sample Selection in Randomized Experiments. EC Yuchen Hu, Henry Zhu, Emma Brunskill, Stefan Wager
2024	A*	`conf`	OPERA: Automatic Offline Policy Evaluation with Re-weighted Aggregates of Multiple Estimators. NeurIPS Allen Nie, Yash Chandak, Christina J. Yuan, Anirudhan Badrinath, Yannis Flet-Berliac, Emma Brunskill
2024	J	`jnl`	OPERA: Automatic Offline Policy Evaluation with Re-weighted Aggregates of Multiple Estimators. CoRR Allen Nie, Yash Chandak, Christina J. Yuan, Anirudhan Badrinath, Yannis Flet-Berliac, Emma Brunskill
2024	J	`jnl`	Predicting Long Term Sequential Policy Value Using Softer Surrogates. CoRR Hyunji Nam, Allen Nie, Ge Gao, Vasilis Syrgkanis, Emma Brunskill
2024	J	`jnl`	Predicting Long-Term Student Outcomes from Short-Term EdTech Log Data. CoRR Ge Gao, Amelia Leon, Andrea Jetten, Jasmine Turner, Husni Almoubayyed, Stephen Fancsali, Emma Brunskill
2024	J	`jnl`	Psychometric Alignment: Capturing Human Knowledge Distributions via Language Models. CoRR Joy He-Yueya, Wanjing Anya Ma, Kanishk Gandhi, Benjamin W. Domingue, Emma Brunskill, Noah D. Goodman
2024	J	`jnl`	Reinforcement learning tutor better supported lower performers in a math task. Mach. Learn. Sherry Ruan, Allen Nie, William Steenbergen, Jiayu He, J. Q. Zhang, Meng Guo, Yao Liu, Kyle Dang Nguyen, Catherine Y. Wang, Rui Ying, James A. Landay, Emma Brunskill
2024	A*	`conf`	Roleplay-doh: Enabling Domain-Experts to Create LLM-simulated Patients via Eliciting and Adhering to Principles. EMNLP Ryan Louie, Ananjan Nandi, William Fang, Cheng Chang, Emma Brunskill, Diyi Yang
2024	J	`jnl`	Roleplay-doh: Enabling Domain-Experts to Create LLM-simulated Patients via Eliciting and Adhering to Principles. CoRR Ryan Louie, Ananjan Nandi, William Fang, Cheng Chang, Emma Brunskill, Diyi Yang
2024	J	`jnl`	Short-Long Policy Evaluation with Novel Actions. CoRR Hyunji Alex Nam, Yash Chandak, Emma Brunskill
2024	J	`jnl`	Supporting Physical Activity Behavior Change with LLM-Based Conversational Agents. CoRR Matthew Jörke, Shardul Sapkota, Lyndsea Warkenthien, Niklas Vainio, Paul Schmiedmayer, Emma Brunskill, James A. Landay
2024	J	`jnl`	The GPT Surprise: Offering Large Language Model Chat in a Massive Coding Class Reduced Engagement but Increased Adopters Exam Performances. CoRR Allen Nie, Yash Chandak, Miroslav Suzara, Ali Malik, Juliette Woodrow, Matt Peng, Mehran Sahami, Emma Brunskill, Chris Piech
2023	J	`jnl`	Adaptive Instrument Design for Indirect Experiments. CoRR Yash Chandak, Shiv Shankar, Vasilis Syrgkanis, Emma Brunskill
2023	J	`jnl`	Adaptive Interventions with User-Defined Goals for Health Behavior Change. CoRR Aishwarya Mandyam, Matthew Jörke, Barbara E. Engelhardt, Emma Brunskill
2023	J	`jnl`	Estimating Optimal Policy Value in General Linear Contextual Bandits. CoRR Jonathan N. Lee, Weihao Kong, Aldo Pacchiano, Vidya Muthukumar, Emma Brunskill
2023	A*	`conf`	Experiment Planning with Function Approximation. NeurIPS Aldo Pacchiano, Jonathan Lee, Emma Brunskill
2023	J	`jnl`	Improving Student Learning with Hybrid Human-AI Tutoring: A Three-Study Quasi-Experimental Investigation. CoRR Danielle R. Thomas, Jionghao Lin, Erin Gatz, Ashish Gurung, Shivang Gupta, Kole Norberg, Stephen E. Fancsali, Vincent Aleven, Lee G. Branstetter, Emma Brunskill, Kenneth R. Koedinger
2023	A*	`ed.`	International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA. ICML Andreas Krause, Emma Brunskill, Kyunghyun Cho, Barbara Engelhardt, Sivan Sabato, Jonathan Scarlett
2023	A*	`conf`	Model-Based Offline Reinforcement Learning with Local Misspecification. AAAI Kefan Dong, Yannis Flet-Berliac, Allen Nie, Emma Brunskill
2023	J	`jnl`	Model-based Offline Reinforcement Learning with Local Misspecification. CoRR Kefan Dong, Yannis Flet-Berliac, Allen Nie, Emma Brunskill
2023	J	`jnl`	Off-Policy Evaluation for Action-Dependent Non-Stationary Environments. CoRR Yash Chandak, Shiv Shankar, Nathaniel D. Bastian, Bruno Castro da Silva, Emma Brunskill, Philip S. Thomas
2023	A*	`conf`	Proportional Response: Contextual Bandits for Simple and Cumulative Regret Minimization. NeurIPS Sanath Kumar Krishnamurthy, Ruohan Zhan, Susan Athey, Emma Brunskill
2023	J	`jnl`	Proportional Response: Contextual Bandits for Simple and Cumulative Regret Minimization. CoRR Sanath Kumar Krishnamurthy, Ruohan Zhan, Susan Athey, Emma Brunskill
2023	J	`jnl`	Reinforcement Learning Tutor Better Supported Lower Performers in a Math Task. CoRR Sherry Ruan, Allen Nie, William Steenbergen, Jiayu He, JQ Zhang, Meng Guo, Yao Liu, Kyle Dang Nguyen, Catherine Y. Wang, Rui Ying, James A. Landay, Emma Brunskill
2023	A*	`conf`	Supervised Pretraining Can Learn In-Context Reinforcement Learning. NeurIPS Jonathan Lee, Annie Xie, Aldo Pacchiano, Yash Chandak, Chelsea Finn, Ofir Nachum, Emma Brunskill
2023	J	`jnl`	Supervised Pretraining Can Learn In-Context Reinforcement Learning. CoRR Jonathan N. Lee, Annie Xie, Aldo Pacchiano, Yash Chandak, Chelsea Finn, Ofir Nachum, Emma Brunskill
2023	—	`conf`	Towards the Future of AI-Augmented Human Tutoring in Math Learning. AIED (Posters/Late Breaking Results/...) Vincent Aleven, Richard G. Baraniuk, Emma Brunskill, Scott A. Crossley, Dora Demszky, Stephen Fancsali, Shivang Gupta, Kenneth R. Koedinger, Chris Piech, Steven Ritter, Danielle R. Thomas, Simon Woodhead, Wanli Xing
2023	—	`conf`	Understanding the Impact of Reinforcement Learning Personalization on Subgroups of Students in Math Tutoring. AIED (Posters/Late Breaking Results/...) Allen Nie, Ann-Katrin Reuel, Emma Brunskill
2023	A*	`conf`	Waypoint Transformer: Reinforcement Learning via Supervised Learning with Intermediate Targets. NeurIPS Anirudhan Badrinath, Yannis Flet-Berliac, Allen Nie, Emma Brunskill
2023	J	`jnl`	Waypoint Transformer: Reinforcement Learning via Supervised Learning with Intermediate Targets. CoRR Anirudhan Badrinath, Yannis Flet-Berliac, Allen Nie, Emma Brunskill
2022	A*	`conf`	Constraint Sampling Reinforcement Learning: Incorporating Expertise for Faster Learning. AAAI Tong Mu, Georgios Theocharous, David Arbour, Emma Brunskill
2022	A*	`conf`	Data-Efficient Pipeline for Offline Reinforcement Learning with Limited Data. NeurIPS Allen Nie, Yannis Flet-Berliac, Deon R. Jordan, William Steenbergen, Emma Brunskill
2022	J	`jnl`	Data-Efficient Pipeline for Offline Reinforcement Learning with Limited Data. CoRR Allen Nie, Yannis Flet-Berliac, Deon R. Jordan, William Steenbergen, Emma Brunskill
2022	A*	`conf`	Factored DRO: Factored Distributionally Robust Policies for Contextual Bandits. NeurIPS Tong Mu, Yash Chandak, Tatsunori B. Hashimoto, Emma Brunskill
2022	A*	`conf`	Giving Feedback on Interactive Student Programs with Meta-Exploration. NeurIPS Evan Zheran Liu, Moritz Stephan, Allen Nie, Chris Piech, Emma Brunskill, Chelsea Finn
2022	J	`jnl`	Giving Feedback on Interactive Student Programs with Meta-Exploration. CoRR Evan Zheran Liu, Moritz Stephan, Allen Nie, Chris Piech, Emma Brunskill, Chelsea Finn
2022	—	`conf`	Identification of Subgroups With Similar Benefits in Off-Policy Policy Evaluation. CHIL Ramtin Keramati, Omer Gottesman, Leo Anthony Celi, Finale Doshi-Velez, Emma Brunskill
2022	A*	`conf`	Off-Policy Evaluation for Action-Dependent Non-stationary Environments. NeurIPS Yash Chandak, Shiv Shankar, Nathaniel D. Bastian, Bruno C. da Silva, Emma Brunskill, Philip S. Thomas
2022	J	`jnl`	Offline Policy Optimization with Eligible Actions. CoRR Yao Liu, Yannis Flet-Berliac, Emma Brunskill
2022	A	`conf`	Offline policy optimization with eligible actions. UAI Yao Liu, Yannis Flet-Berliac, Emma Brunskill
2022	A*	`conf`	Oracle Inequalities for Model Selection in Offline Reinforcement Learning. NeurIPS Jonathan N. Lee, George Tucker, Ofir Nachum, Bo Dai, Emma Brunskill
2022	J	`jnl`	Oracle Inequalities for Model Selection in Offline Reinforcement Learning. CoRR Jonathan N. Lee, George Tucker, Ofir Nachum, Bo Dai, Emma Brunskill
2021	B	`conf`	Automatic Adaptive Sequencing in a Webgame. ITS Tong Mu, Shuhan Wang, Erik Andersen, Emma Brunskill
2021	J	`jnl`	Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning. CoRR Tong Mu, Georgios Theocharous, David Arbour, Emma Brunskill
2021	A*	`conf`	Design of Experiments for Stochastic Contextual Linear Bandits. NeurIPS Andrea Zanette, Kefan Dong, Jonathan N. Lee, Emma Brunskill
2021	J	`jnl`	Design of Experiments for Stochastic Contextual Linear Bandits. CoRR Andrea Zanette, Kefan Dong, Jonathan N. Lee, Emma Brunskill
2021	A	`conf`	EnglishBot: An AI-Powered Conversational System for Second Language Learning. IUI Sherry Ruan, Liwei Jiang, Qianyao Xu, Zhiyuan Liu, Glenn M. Davis, Emma Brunskill, James A. Landay
2021	J	`jnl`	Identification of Subgroups With Similar Benefits in Off-Policy Policy Evaluation. CoRR Ramtin Keramati, Omer Gottesman, Leo Anthony Celi, Finale Doshi-Velez, Emma Brunskill
2021	J	`jnl`	Learning to be Fair: A Consequentialist Approach to Equitable Decision-Making. CoRR Alex Chohlas-Wood, Madison Coots, Emma Brunskill, Sharad Goel
2021	J	`jnl`	On the Opportunities and Risks of Foundation Models. CoRR Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ B. Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri S. Chatterji, Annie S. Chen, Kathleen Creel, Jared Quincy Davis, Dorottya Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren E. Gillespie, Karan Goel, Noah D. Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark S. Krass, Ranjay Krishna, Rohith Kuditipudi, et al.
2021	A	`conf`	Online Model Selection for Reinforcement Learning with Function Approximation. AISTATS Jonathan N. Lee, Aldo Pacchiano, Vidya Muthukumar, Weihao Kong, Emma Brunskill
2021	A*	`conf`	Play to Grade: Testing Coding Games as Classifying Markov Decision Process. NeurIPS Allen Nie, Emma Brunskill, Chris Piech
2021	J	`jnl`	Play to Grade: Testing Coding Games as Classifying Markov Decision Process. CoRR Allen Nie, Emma Brunskill, Chris Piech
2021	—	`conf`	Power Constrained Bandits. MLHC Jiayu Yao, Emma Brunskill, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez
2021	A*	`conf`	Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning. NeurIPS Andrea Zanette, Martin J. Wainwright, Emma Brunskill
2021	J	`jnl`	Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning. CoRR Andrea Zanette, Martin J. Wainwright, Emma Brunskill
2021	A*	`conf`	Reinforcement Learning with State Observation Costs in Action-Contingent Noiselessly Observable Markov Decision Processes. NeurIPS Hyunji Alex Nam, Scott L. Fleming, Emma Brunskill
2021	A*	`conf`	Universal Off-Policy Evaluation. NeurIPS Yash Chandak, Scott Niekum, Bruno C. da Silva, Erik G. Learned-Miller, Emma Brunskill, Philip S. Thomas
2021	J	`jnl`	Universal Off-Policy Evaluation. CoRR Yash Chandak, Scott Niekum, Bruno Castro da Silva, Erik G. Learned-Miller, Emma Brunskill, Philip S. Thomas
2020	A*	`conf`	Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy. AAAI Ramtin Keramati, Christoph Dann, Alex Tamkin, Emma Brunskill
2020	A	`conf`	Frequentist Regret Bounds for Randomized Least-Squares Value Iteration. AISTATS Andrea Zanette, David Brandfonbrener, Emma Brunskill, Matteo Pirotta, Alessandro Lazaric
2020	A*	`conf`	Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions. ICML Omer Gottesman, Joseph Futoma, Yao Liu, Sonali Parbhoo, Leo A. Celi, Emma Brunskill, Finale Doshi-Velez
2020	J	`jnl`	Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions. CoRR Omer Gottesman, Joseph Futoma, Yao Liu, Sonali Parbhoo, Leo Anthony Celi, Emma Brunskill, Finale Doshi-Velez
2020	J	`jnl`	Learning Abstract Models for Strategic Exploration and Fast Reward Transfer. CoRR Evan Zheran Liu, Ramtin Keramati, Sudarshan Seshadri, Kelvin Guu, Panupong Pasupat, Emma Brunskill, Percy Liang
2020	A*	`conf`	Learning Near Optimal Policies with Low Inherent Bellman Error. ICML Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill
2020	J	`jnl`	Learning Near Optimal Policies with Low Inherent Bellman Error. CoRR Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill
2020	A*	`conf`	Off-policy Policy Evaluation For Sequential Decisions Under Unobserved Confounding. NeurIPS Hongseok Namkoong, Ramtin Keramati, Steve Yadlowsky, Emma Brunskill
2020	J	`jnl`	Off-policy Policy Evaluation For Sequential Decisions Under Unobserved Confounding. CoRR Hongseok Namkoong, Ramtin Keramati, Steve Yadlowsky, Emma Brunskill
2020	J	`jnl`	Online Model Selection for Reinforcement Learning with Function Approximation. CoRR Jonathan N. Lee, Aldo Pacchiano, Vidya Muthukumar, Weihao Kong, Emma Brunskill
2020	J	`jnl`	Power-Constrained Bandits. CoRR Jiayu Yao, Emma Brunskill, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez
2020	A*	`conf`	Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration. NeurIPS Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill
2020	J	`jnl`	Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration. CoRR Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill
2020	A*	`conf`	Provably Good Batch Off-Policy Reinforcement Learning Without Great Exploration. NeurIPS Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill
2020	J	`jnl`	Provably Good Batch Reinforcement Learning Without Great Exploration. CoRR Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill
2020	A	`conf`	Sublinear Optimal Policy Value Estimation in Contextual Bandits. AISTATS Weihao Kong, Emma Brunskill, Gregory Valiant
2020	Misc	`conf`	Supporting children's math learning with feedback-augmented narrative technology. IDC Sherry Ruan, Jiayu He, Rui Ying, Jonathan Burkle, Dunia Hakim, Anna Wang, Yufeng Yin, Lily Zhou, Qianyao Xu, Abdallah A. AbuHashem, Griffin Dietz, Elizabeth L. Murnane, Emma Brunskill, James A. Landay
2020	B	`conf`	Towards Suggesting Actionable Interventions for Wheel Spinning Students. EDM Tong Mu, Andrea Jetten, Emma Brunskill
2020	J	`jnl`	Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning. CoRR Peter Henderson, Jieru Hu, Joshua Romoff, Emma Brunskill, Dan Jurafsky, Joelle Pineau
2020	A*	`conf`	Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance Sampling. ICML Yao Liu, Pierre-Luc Bacon, Emma Brunskill
2020	J	`jnl`	Value Driven Representation for Human-in-the-Loop Reinforcement Learning. CoRR Ramtin Keramati, Emma Brunskill
2019	A*	`conf`	Almost Horizon-Free Structure-Aware Best Policy Identification with a Generative Model. NeurIPS Andrea Zanette, Mykel J. Kochenderfer, Emma Brunskill
2019	J	`jnl`	Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy. CoRR Ramtin Keramati, Christoph Dann, Alex Tamkin, Emma Brunskill
2019	B	`conf`	BookBuddy: Turning Digital Materials Into Interactive Foreign Language Lessons Through a Voice Chatbot. L@S Sherry Ruan, Angelica Willis, Qianyao Xu, Glenn M. Davis, Liwei Jiang, Emma Brunskill, James A. Landay
2019	J	`jnl`	Combining Parametric and Nonparametric Models for Off-Policy Evaluation. CoRR Omer Gottesman, Yao Liu, Scott Sussex, Emma Brunskill, Finale Doshi-Velez
2019	A*	`conf`	Combining parametric and nonparametric models for off-policy evaluation. ICML Omer Gottesman, Yao Liu, Scott Sussex, Emma Brunskill, Finale Doshi-Velez
2019	J	`jnl`	Directed Exploration for Reinforcement Learning. CoRR Zhaohan Daniel Guo, Emma Brunskill
2019	A	`conf`	Fairer but Not Fair Enough On the Equitability of Knowledge Tracing. LAK Shayan Doroudi, Emma Brunskill
2019	A	`conf`	Fake It Till You Make It: Learning-Compatible Performance Support. UAI Jonathan Bragg, Emma Brunskill
2019	B	`conf`	Key Phrase Extraction for Generating Educational Question-Answer Pairs. L@S Angelica Willis, Glenn M. Davis, Sherry Ruan, Lakshmi Manoharan, James A. Landay, Emma Brunskill
2019	—	`conf`	Learning Procedural Abstractions and Evaluating Discrete Latent Temporal Structure. ICLR (Poster) Karan Goel, Emma Brunskill
2019	A*	`conf`	Limiting Extrapolation in Linear Approximate Value Iteration. NeurIPS Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill
2019	J	`jnl`	Missingness as Stability: Understanding the Structure of Missingness in Longitudinal EHR data and its Impact on Reinforcement Learning in Healthcare. CoRR Scott L. Fleming, Kuhan Jeyapragasan, Tony Duan, Daisy Yi Ding, Saurabh Gombar, Nigam Shah, Emma Brunskill
2019	B	`conf`	Not Everyone Writes Good Examples but Good Examples Can Come from Anywhere. HCOMP Shayan Doroudi, Ece Kamar, Emma Brunskill
2019	J	`jnl`	Off-Policy Policy Gradient with State Distribution Correction. CoRR Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill
2019	A	`conf`	Off-Policy Policy Gradient with Stationary Distribution Correction. UAI Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill
2019	A*	`conf`	Offline Contextual Bandits with High Probability Fairness Guarantees. NeurIPS Blossom Metevier, Stephen Giguere, Sarah Brockman, Ari Kobren, Yuriy Brun, Emma Brunskill, Philip S. Thomas
2019	J	`jnl`	PLOTS: Procedure Learning from Observations using Subtask Structure. CoRR Tong Mu, Karan Goel, Emma Brunskill
2019	A	`conf`	PLOTS: Procedure Learning from Observations using subTask Structure. AAMAS Tong Mu, Karan Goel, Emma Brunskill
2019	A*	`conf`	Policy Certificates: Towards Accountable Reinforcement Learning. ICML Christoph Dann, Lihong Li, Wei Wei, Emma Brunskill
2019	J	`jnl`	Problem Dependent Reinforcement Learning Bounds Which Can Identify Bandit Structure in MDPs. CoRR Andrea Zanette, Emma Brunskill
2019	A*	`conf`	QuizBot: A Dialogue-based Adaptive Learning System for Factual Knowledge. CHI Sherry Ruan, Liwei Jiang, Justin Xu, Bryce Joe-Kun Tham, Zhengneng Qiu, Yeshuang Zhu, Elizabeth L. Murnane, Emma Brunskill, James A. Landay
2019	A*	`conf`	Separable value functions across time-scales. ICML Joshua Romoff, Peter Henderson, Ahmed Touati, Yann Ollivier, Joelle Pineau, Emma Brunskill
2019	J	`jnl`	Separating value functions across time-scales. CoRR Joshua Romoff, Peter Henderson, Ahmed Touati, Yann Ollivier, Emma Brunskill, Joelle Pineau
2019	J	`jnl`	Sublinear Optimal Policy Value Estimation in Contextual Bandits. CoRR Weihao Kong, Gregory Valiant, Emma Brunskill
2019	A*	`conf`	Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds. ICML Andrea Zanette, Emma Brunskill
2019	J	`jnl`	Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds. CoRR Andrea Zanette, Emma Brunskill
2019	J	`jnl`	Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance Sampling. CoRR Yao Liu, Pierre-Luc Bacon, Emma Brunskill
2019	A	`conf`	Value Driven Representation for Human-in-the-Loop Reinforcement Learning. UMAP Ramtin Keramati, Emma Brunskill
2019	J	`jnl`	Where's the Reward? Int. J. Artif. Intell. Educ. Shayan Doroudi, Vincent Aleven, Emma Brunskill
2018	B	`conf`	Adaptive natural-language targeting for student feedback. L@S Y. Alex Kolchinski, Sherry Ruan, Dan Schwartz, Emma Brunskill
2018	J	`jnl`	Behaviour Policy Estimation in Off-Policy Policy Evaluation: Calibration Matters. CoRR Aniruddh Raghu, Omer Gottesman, Yao Liu, Matthieu Komorowski, Aldo Faisal, Finale Doshi-Velez, Emma Brunskill
2018	B	`conf`	Combining adaptivity with progression ordering for intelligent tutoring systems. L@S Tong Mu, Shuhan Wang, Erik Andersen, Emma Brunskill
2018	A*	`conf`	Decoupling Gradient-Like Learning Rules from Representations. ICML Philip S. Thomas, Christoph Dann, Emma Brunskill
2018	J	`jnl`	Distilling Information from a Flood: A Possibility for the Use of Meta-Analysis and Systematic Review in Machine Learning Research. CoRR Peter Henderson, Emma Brunskill
2018	Misc	`conf`	Efficient Exploration Through Bayesian Deep Q-Networks. ITA Kamyar Azizzadenesheli, Emma Brunskill, Animashree Anandkumar
2018	J	`jnl`	Efficient Exploration through Bayesian Deep Q-Networks. CoRR Kamyar Azizzadenesheli, Emma Brunskill, Animashree Anandkumar
2018	B	`conf`	Exploring the impact of the default option on student engagement and performance in a statistics MOOC. L@S Emma Brunskill, Dawn Zimmaro, Candace Thille
2018	A*	`conf`	Importance Sampling for Fair Policy Selection. IJCAI Shayan Doroudi, Philip S. Thomas, Emma Brunskill
2018	J	`jnl`	Policy Certificates: Towards Accountable Reinforcement Learning. CoRR Christoph Dann, Lihong Li, Wei Wei, Emma Brunskill
2018	A*	`conf`	Problem Dependent Reinforcement Learning Bounds Which Can Identify Bandit Structure in MDPs. ICML Andrea Zanette, Emma Brunskill
2018	J	`jnl`	Representation Balancing MDPs for Off-Policy Policy Evaluation. CoRR Yao Liu, Omer Gottesman, Aniruddh Raghu, Matthieu Komorowski, Aldo Faisal, Finale Doshi-Velez, Emma Brunskill
2018	A*	`conf`	Representation Balancing MDPs for Off-policy Policy Evaluation. NeurIPS Yao Liu, Omer Gottesman, Aniruddh Raghu, Matthieu Komorowski, Aldo A. Faisal, Finale Doshi-Velez, Emma Brunskill
2018	J	`jnl`	Sample-Efficient Deep RL with Generative Adversarial Tree Search. CoRR Kamyar Azizzadenesheli, Brandon Yang, Weitang Liu, Emma Brunskill, Zachary C. Lipton, Animashree Anandkumar
2018	—	`conf`	Shared Autonomy for an Interactive AI System. UIST (Adjunct Volume) Sharon Zhou, Tong Mu, Karan Goel, Michael S. Bernstein, Emma Brunskill
2018	J	`jnl`	Strategic Object Oriented Reinforcement Learning. CoRR Ramtin Keramati, Jay Whang, Patrick Cho, Emma Brunskill
2018	J	`jnl`	When Simple Exploration is Sample Efficient: Identifying Sufficient Conditions for Random Exploration to Yield PAC RL Algorithms. CoRR Yao Liu, Emma Brunskill
2017	J	`jnl`	Decoupling Learning Rules from Representations. CoRR Philip S. Thomas, Christoph Dann, Emma Brunskill
2017	J	`jnl`	Generalized Grounding Graphs: A Probabilistic Framework for Understanding Grounded Commands. CoRR Thomas Kollar, Stefanie Tellex, Matthew R. Walter, Albert Huang, Abraham Bachrach, Sachithra Hemachandra, Emma Brunskill, Ashis Gopal Banerjee, Deb Roy, Seth J. Teller, Nicholas Roy
2017	A	`conf`	Importance Sampling for Fair Policy Selection. UAI Shayan Doroudi, Philip S. Thomas, Emma Brunskill
2017	A*	`conf`	Importance Sampling with Unequal Support. AAAI Philip S. Thomas, Emma Brunskill
2017	J	`jnl`	On Ensuring that Intelligent Machines Are Well-Behaved. CoRR Philip S. Thomas, Bruno Castro da Silva, Andrew G. Barto, Emma Brunskill
2017	J	`jnl`	Policy Gradient Methods for Reinforcement Learning with Function Approximation and Action-Dependent Baselines. CoRR Philip S. Thomas, Emma Brunskill
2017	A*	`conf`	Predictive Off-Policy Policy Evaluation for Nonstationary Decision Problems, with Applications to Digital Marketing. AAAI Philip S. Thomas, Georgios Theocharous, Mohammad Ghavamzadeh, Ishan Durugkar, Emma Brunskill
2017	—	`conf`	Regret Minimization in MDPs with Options without Prior Knowledge. NIPS Ronan Fruit, Matteo Pirotta, Alessandro Lazaric, Emma Brunskill
2017	B	`conf`	Robust Evaluation Matrix: Towards a More Principled Offline Exploration of Instructional Policies. L@S Shayan Doroudi, Vincent Aleven, Emma Brunskill
2017	J	`jnl`	Sample Efficient Feature Selection for Factored MDPs. CoRR Zhaohan Daniel Guo, Emma Brunskill
2017	A*	`conf`	Sample Efficient Policy Search for Optimal Stopping Domains. IJCAI Karan Goel, Christoph Dann, Emma Brunskill
2017	J	`jnl`	Sample Efficient Policy Search for Optimal Stopping Domains. CoRR Karan Goel, Christoph Dann, Emma Brunskill
2017	B	`conf`	The Misidentified Identifiability Problem of Bayesian Knowledge Tracing. EDM Shayan Doroudi, Emma Brunskill
2017	A	`conf`	Trading off Rewards and Errors in Multi-Armed Bandits. AISTATS Akram Erraqabi, Alessandro Lazaric, Michal Valko, Emma Brunskill, Yun-En Liu
2017	J	`jnl`	UBEV - A More Practical Algorithm for Episodic RL with Near-Optimal PAC and Regret Guarantees. CoRR Christoph Dann, Tor Lattimore, Emma Brunskill
2017	—	`conf`	Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning. NIPS Christoph Dann, Tor Lattimore, Emma Brunskill
2017	—	`conf`	Using Options and Covariance Testing for Long Horizon Off-Policy Policy Evaluation. NIPS Zhaohan Guo, Philip S. Thomas, Emma Brunskill
2017	J	`jnl`	Using Options for Long-Horizon Off-Policy Evaluation. CoRR Zhaohan Daniel Guo, Philip S. Thomas, Emma Brunskill
2017	A*	`conf`	Where to Add Actions in Human-in-the-Loop Reinforcement Learning. AAAI Travis Mandel, Yun-En Liu, Emma Brunskill, Zoran Popovic
2016	A	`conf`	A PAC RL Algorithm for Episodic POMDPs. AISTATS Zhaohan Daniel Guo, Shayan Doroudi, Emma Brunskill
2016	J	`jnl`	A PAC RL Algorithm for Episodic POMDPs. CoRR Zhaohan Daniel Guo, Shayan Doroudi, Emma Brunskill
2016	B	`conf`	Automatically Learning to Teach to the Learning Objectives. L@S Rika Antonova, Joe Runde, Min Hyung Lee, Emma Brunskill
2016	A*	`conf`	Data-Efficient Off-Policy Policy Evaluation for Reinforcement Learning. ICML Philip S. Thomas, Emma Brunskill
2016	J	`jnl`	Data-Efficient Off-Policy Policy Evaluation for Reinforcement Learning. CoRR Philip S. Thomas, Emma Brunskill
2016	A*	`conf`	Efficient Bayesian Clustering for Reinforcement Learning. IJCAI Travis Mandel, Yun-En Liu, Emma Brunskill, Zoran Popovic
2016	A*	`conf`	Energetic Natural Gradient Descent. ICML Philip S. Thomas, Bruno Castro da Silva, Christoph Dann, Emma Brunskill
2016	J	`jnl`	Faster Teaching via POMDP Planning. Cogn. Sci. Anna N. Rafferty, Emma Brunskill, Thomas L. Griffiths, Patrick Shafto
2016	J	`jnl`	Importance Sampling with Unequal Support. CoRR Philip S. Thomas, Emma Brunskill
2016	A*	`conf`	Interface Design Optimization as a Multi-Armed Bandit Problem. CHI James Derek Lomas, Jodi Forlizzi, Nikhil Poonwala, Nirmal Patel, Sharan Shodhan, Kishan Patel, Kenneth R. Koedinger, Emma Brunskill
2016	A*	`conf`	Latent Contextual Bandits and their Application to Personalized Recommendations for New Users. IJCAI Li Zhou, Emma Brunskill
2016	J	`jnl`	Latent Contextual Bandits and their Application to Personalized Recommendations for New Users. CoRR Li Zhou, Emma Brunskill
2016	A*	`conf`	Offline Evaluation of Online Reinforcement Learning Algorithms. AAAI Travis Mandel, Yun-En Liu, Emma Brunskill, Zoran Popovic
2016	A	`conf`	PAC Continuous State Online Multitask Reinforcement Learning with Identification. AAMAS Yao Liu, Zhaohan Guo, Emma Brunskill
2016	A*	`conf`	Questimator: Generating Knowledge Assessments for Arbitrary Topics. IJCAI Qi Guo, Chinmay Kulkarni, Aniket Kittur, Jeffrey P. Bigham, Emma Brunskill
2016	—	`conf`	Sequence Matters, But How Do I Discover How? Towards a Workflow for Evaluating Activity Sequences from Data. EDM (Workshops) Shayan Doroudi, Kenneth Holstein, Vincent Aleven, Emma Brunskill
2016	B	`conf`	Sequence Matters, But How Exactly? A Method for Evaluating Activity Sequences from Data. EDM Shayan Doroudi, Kenneth Holstein, Vincent Aleven, Emma Brunskill
2016	A*	`conf`	Toward a Learning Science for Complex Crowdsourcing Tasks. CHI Shayan Doroudi, Ece Kamar, Emma Brunskill, Eric Horvitz
2015	A*	`conf`	Concurrent PAC RL. AAAI Zhaohan Guo, Emma Brunskill
2015	B	`conf`	From Predictive Models to Instructional Policies. EDM Joseph Rollinson, Emma Brunskill
2015	B	`conf`	Learning the Features Used To Decide How to Teach. L@S Min Hyung Lee, Joe Runde, Warfa Jibril, Zhuoying Wang, Emma Brunskill
2015	—	`conf`	Sample Complexity of Episodic Fixed-Horizon Reinforcement Learning. NIPS Christoph Dann, Emma Brunskill
2015	J	`jnl`	Sample Complexity of Episodic Fixed-Horizon Reinforcement Learning. CoRR Christoph Dann, Emma Brunskill
2015	J	`jnl`	The Online Discovery Problem and Its Application to Lifelong Reinforcement Learning. CoRR Emma Brunskill, Lihong Li
2015	A*	`conf`	The Queue Method: Handling Delay, Heuristics, Prior Data, and Evaluation in Bandits. AAAI Travis Mandel, Yun-En Liu, Emma Brunskill, Zoran Popovic
2015	B	`conf`	Towards Understanding How to Leverage Sense-making, Induction/Refinement and Fluency to Improve Robust Learning. EDM Shayan Doroudi, Kenneth Holstein, Vincent Aleven, Emma Brunskill
2014	J	`jnl`	Efficient Planning under Uncertainty with Macro-actions. CoRR Ruijie He, Emma Brunskill, Nicholas Roy
2014	A	`conf`	Offline policy evaluation across representations with applications to educational games. AAMAS Travis Mandel, Yun-En Liu, Sergey Levine, Emma Brunskill, Zoran Popovic
2014	A*	`conf`	Online Stochastic Optimization under Correlated Bandit Feedback. ICML Mohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill
2014	A*	`conf`	PAC-inspired Option Discovery in Lifelong Reinforcement Learning. ICML Emma Brunskill, Lihong Li
2014	—	`conf`	Quantifying Uncertainty in Batch Personalized Sequential Decision Making. AAAI Workshop: Modern Artificial Intelligence for Health Analytics Vukosi Marivate, Jessica Chemali, Emma Brunskill, Michael L. Littman
2014	J	`jnl`	Stochastic Optimization of a Locally Smooth Function under Correlated Bandit Feedback. CoRR Mohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill
2014	A*	`conf`	Towards automatic experimentation of educational knowledge. CHI Yun-En Liu, Travis Mandel, Emma Brunskill, Zoran Popovic
2014	B	`conf`	Trading Off Scientific Knowledge and User Learning with Multi-Armed Bandits. EDM Yun-En Liu, Travis Mandel, Emma Brunskill, Zoran Popovic
2013	—	`conf`	Analysis of the impact of errors made during health data collection using mobile phones: exploring error modeling and automatic diagnosis. ACM DEV (3) Sukhada Palkar, Emma Brunskill
2013	B	`conf`	Estimating Student Knowledge from Paired Interaction Data. EDM Anna N. Rafferty, Jodi L. Davenport, Emma Brunskill
2013	—	`conf`	Modeling Social Information Learning among Taxi Drivers. PAKDD (2) Siyuan Liu, Ramayya Krishnan, Emma Brunskill, Lionel M. Ni
2013	J	`jnl`	New Potentials for Data-Driven Intelligent Tutoring System Development and Optimization. AI Mag. Kenneth R. Koedinger, Emma Brunskill, Ryan Shaun Joazeiro de Baker, Elizabeth A. McLaughlin, John C. Stamper
2013	B	`conf`	Predicting Player Moves in an Educational Game: A Hybrid Approach. EDM Yun-En Liu, Travis Mandel, Eric Butler, Erik Andersen, Eleanor O'Rourke, Emma Brunskill, Zoran Popovic
2013	J	`jnl`	Regret Bounds for Reinforcement Learning with Policy Advice CoRR Mohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill
2013	—	`conf`	Regret Bounds for Reinforcement Learning with Policy Advice. ECML/PKDD (1) Mohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill
2013	A	`conf`	Sample Complexity of Multi-task Reinforcement Learning. UAI Emma Brunskill, Lihong Li
2013	J	`jnl`	Sample Complexity of Multi-task Reinforcement Learning. CoRR Emma Brunskill, Lihong Li
2013	—	`conf`	Sequential Transfer in Multi-armed Bandit with Finite Set of Models. NIPS Mohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill
2013	J	`jnl`	Sequential Transfer in Multi-armed Bandit with Finite Set of Models. CoRR Mohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill
2013	—	`conf`	Towards operationalizing outlier detection in community health programs. ICTD (2) Ted McCarthy, Brian DeRenzi, Joshua Evan Blumenstock, Emma Brunskill
2013	—	`conf`	Understanding Sequential Decisions via Inverse Reinforcement Learning. MDM (1) Siyuan Liu, Miguel Araujo, Emma Brunskill, Rosaldo J. F. Rossetti, João Barros, Ramayya Krishnan
2012	A	`conf`	Bayes-optimal reinforcement learning for discrete uncertainty domains. AAMAS Emma Brunskill
2012	J	`jnl`	CORL: A Continuous-state Offset-dynamics Reinforcement Learner CoRR Emma Brunskill, Bethany R. Leffler, Lihong Li, Michael L. Littman, Nicholas Roy
2012	J	`jnl`	Incentive Decision Processes CoRR Sashank Jakkam Reddi, Emma Brunskill
2012	A	`conf`	Incentive Decision Processes. UAI Sashank Jakkam Reddi, Emma Brunskill
2012	B	`conf`	Policy Building - An Extension To User Modeling. EDM Michael Yudelson, Emma Brunskill
2012	J	`jnl`	RAPID: A Reachable Anytime Planner for Imprecisely-sensed Domains CoRR Emma Brunskill, Stuart Russell
2012	B	`conf`	The Impact on Individualizing Student Models on Necessary Practice Opportunities. EDM Jung In Lee, Emma Brunskill
2011	J	`jnl`	Designing mobile interfaces for novice and low-literacy users. ACM Trans. Comput. Hum. Interact. Indrani Medhi, Somani Patnaik, Emma Brunskill, S. N. Nagasena Gautama, William Thies, Kentaro Toyama
2011	J	`jnl`	Efficient Planning under Uncertainty with Macro-actions. J. Artif. Intell. Res. Ruijie He, Emma Brunskill, Nicholas Roy
2011	B	`conf`	Estimating Prerequisite Structure From Noisy Data. EDM Emma Brunskill
2011	A	`conf`	Faster Teaching by POMDP Planning. AIED Anna N. Rafferty, Emma Brunskill, Thomas L. Griffiths, Patrick Shafto
2011	B	`conf`	Partially Observable Sequential Decision Making for Problem Selection in an Intelligent Tutoring System. EDM Emma Brunskill, Stuart Russell
2010	—	`conf`	Learning to Identify Locally Actionable Health Anomalies. AAAI Spring Symposium: Artificial Intelligence for Development Kuang Chen, Emma Brunskill, Jonathan J. Dick, Prabhjot Dhadialla
2010	A*	`conf`	PUMA: Planning Under Uncertainty with Macro-Actions. AAAI Ruijie He, Emma Brunskill, Nicholas Roy
2010	J	`jnl`	Planning in partially-observable switching-mode continuous domains. Ann. Math. Artif. Intell. Emma Brunskill, Leslie Pack Kaelbling, Tomás Lozano-Pérez, Nicholas Roy
2010	A	`conf`	RAPID: A Reachable Anytime Planner for Imprecisely-sensed Domains. UAI Emma Brunskill, Stuart Russell
2010	—	`conf`	Routing for Rural Health: Optimizing Community Health Worker Visit Schedules. AAAI Spring Symposium: Artificial Intelligence for Development Emma Brunskill, Neal Lesh
2010	A*	`conf`	When Policies Can Be Trusted: Analyzing a Criteria to Identify Optimal Policies in MDPs with Unknown Model Parameters. ICAPS Emma Brunskill
2009	—	`—`	Compact parametric models for efficient sequential decision making in high-dimensional, uncertain domains. Emma Brunskill
2009	C	`conf`	Evaluating the accuracy of data collection on mobile phones: A study of forms, SMS, and voice. ICTD Somani Patnaik, Emma Brunskill, William Thies
2009	J	`jnl`	Provably Efficient Learning with Typed Parametric Models. J. Mach. Learn. Res. Emma Brunskill, Bethany R. Leffler, Lihong Li, Michael L. Littman, Nicholas Roy
2009	A*	`conf`	Where to go: Interpreting natural directions using global inference. ICRA Yuan Wei, Emma Brunskill, Thomas Kollar, Nicholas Roy
2008	A	`conf`	CORL: A Continuous-state Offset-dynamics Reinforcement Learner. UAI Emma Brunskill, Bethany R. Leffler, Lihong Li, Michael L. Littman, Nicholas Roy
2008	Misc	`conf`	Continuous-State POMDPs with Hybrid Dynamics. ISAIM Emma Brunskill, Leslie Pack Kaelbling, Tomás Lozano-Pérez, Nicholas Roy
2007	A	`conf`	Collision detection in legged locomotion using supervised learning. IROS Finale Doshi, Emma Brunskill, Alexander C. Shkolnik, Thomas Kollar, Khashayar Rohanimanesh, Russ Tedrake, Nicholas Roy
2007	A*	`conf`	Continuous State POMDPs for Object Manipulation Tasks. AAAI Emma Brunskill
2007	A	`conf`	Topological mapping using spectral clustering and classification. IROS Emma Brunskill, Thomas Kollar, Nicholas Roy
2005	A*	`conf`	SLAM using Incremental Probabilistic PCA and Dimensionality Reduction. ICRA Emma Brunskill, Nicholas Roy
2001	A	`conf`	Building peer-to-peer systems with Chord, a distributed lookup service. HotOS Frank Dabek, Emma Brunskill, M. Frans Kaashoek, David R. Karger, Robert Morris, Ion Stoica, Hari Balakrishnan