PRISE: Learning Temporal Action Abstractions as a Sequence Compression Problem
Ruijie Zheng, Ching-An Cheng, Hal Daumé III, Furong Huang, Andrey Kolobov
ICML 2024 | February 2024
Hal Daumé III
Principal Researcher
Publications
Publications by Year
-
PRISE: Learning Temporal Action Abstractions as a Sequence Compression Problem
Ruijie Zheng, Ching-An Cheng, Hal Daumé III, Furong Huang, Andrey Kolobov
ICML 2024 | February 2024
Premier-TACO is a Few-Shot Policy Learner: Pretraining Multitask Representation via Temporal Action-Driven Contrastive Loss
Ruijie Zheng, Yongyuan Liang, Xiyao Wang, Shuang Ma, Hal Daumé III, Huazhe Xu, John Langford, Praveen Palanisamy, Kalyan Shankar Basu, Furong Huang
ICML 2024 | February 2024
-
Define, Evaluate, and Improve Task-Oriented Cognitive Capabilities for Instruction Generation Models
Lingjun Zhao, Khanh Nguyen, Hal Daumé III
ACL 2023 | May 2023
-
A Framework for Learning to Request Rich and Contextually Useful Information from Humans
Khanh Nguyen, Yonatan Bisk, Hal Daumé III
ICML 2022 | July 2022
Promoting Fairness in Learned Models by Learning to Active Learn under Parity Constraints
Amr Sharaf, Hal Daumé III, Renkun Ni
FAccT 2022 | June 2022
Deconstructing NLG Evaluation: Evaluation Practices, Assumptions, and Their Implications
Kaitlyn Zhou, Su Lin Blodgett, Adam Trischler, Hal Daumé III, Kaheer Suleman, Alexandra Olteanu
NAACL 2022 | May 2022
-
Datasheets for Datasets
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III, Kate Crawford
Communications of the ACM | December 2021, Vol 64(12): pp. 86-92
Distantly-Supervised Evidence Retrieval Enables Question Answering without Evidence Annotation
Chen Zhao, Chenyan Xiong, Jordan Boyd-Graber, Hal Daumé III
2021 Empirical Methods in Natural Language Processing | October 2021
From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence
David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna Wallach, Jennifer Wortman Vaughan
HCOMP 2021 | September 2021
Responsible computing during COVID-19 and beyond
Solon Barocas, Asia J. Biega, Margarita Boyarskaya, Kate Crawford, Hal Daumé III, Miro Dudík, Benjamin Fish, Mary L. Gray, Brent Hecht, Alexandra Olteanu, Forough Poursabzi-Sangdeh, Luke Stark, Jennifer Wortman Vaughan, Hanna Wallach, Marion Zepf
Communications of the ACM | July 2021, Vol 67(7): pp. 30-32
https://doi.org/10.1145/3466612
Multi-Step Reasoning Over Unstructured Text with Beam Dense Retrieval
Chen Zhao, Chenyan Xiong, Jordan L. Boyd-Graber, Hal Daumé III
April 2021
-
Operationalizing the Legal Principle of Data Minimization for Personalization
Asia J. Biega, Peter Potash, Hal Daumé III, Fernando Diaz, Michèle Finck
SIGIR 2020 | July 2020
Language (Technology) is Power: A Critical Survey of “Bias” in NLP
Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna Wallach
ACL | June 2020
Active Imitation Learning With Noisy Guidance
Kianté Brantley, Amr Sharaf, Hal Daumé III
May 2020
Towards Automatic Generation Of Questions From Long Answers
Shlok Kumar Mishra, Pranav Goel, Abhishek Sharma, Abhyuday Jagannatha, David Jacobs, Hal Daumé III
April 2020
Meta-Learning For Few-Shot NMT Adaptation
Amr Sharaf, Hany Hassan Awadalla, Hal Daumé III
April 2020
-
Weight of Evidence as a Basis for Human-Oriented Explanations
David Alvarez-Melis, Hal Daumé III, Jennifer Wortman Vaughan, Hanna Wallach
Workshop on Human-Centric Machine Learning at the 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada. | October 2019
Improving fairness in machine learning systems: What do industry practitioners need?
Ken Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miro Dudík, Hanna Wallach
2019 ACM CHI Conference on Human Factors in Computing Systems | June 2019
Active Learning for Cost-Sensitive Classification
Akshay Krishnamurthy, Alekh Agarwal, Tzu-Kuo Huang, John Langford, Hal Daumé III
Journal of Machine Learning Research | April 2019
Logarithmic Time One-Against-Some
Hal Daumé III, Nikos Karampatziakis, John Langford, Paul Mineiro
ICML 2017 | April 2019
Contextual Memory Trees
Wen Sun, Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro
February 2019
Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback
Chicheng Zhang, Alekh Agarwal, Hal Daumé III, John Langford, Sahand N Negahban
January 2019
-
Hierarchical Imitation and Reinforcement Learning
Hoang M Le, Nan Jiang, Alekh Agarwal, Miro Dudík, Yisong Yue, Hal Daumé III
International Conference on Machine Learning (ICML) | July 2018
International Conference on Machine Learning
-
A Credit Assignment Compiler for Joint Prediction
Kai-Wei Chang, He He, Hal Daumé III, John Langford, Stephane Ross
June 2016
-
Learning to Search Better Than Your Teacher
Kai-Wei Chang, Akshay Krishnamurthy, Alekh Agarwal, Hal Daumé III, John Langford
International Conference on Machine Learning | July 2015
International Conference on Machine Learning
Learning to Search Better than Your Teacher
Kai-Wei Chang, Akshay Krishnamurthy, Alekh Agarwal, John Langford, Hal Daumé III
International Conference on Machine Learning | July 2015
Learning to Search for Dependencies
Kai-Wei Chang, He He, Hal Daumé III, John Langford
May 2015
Learning Reductions that Really Work
Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro
February 2015
-
Search-based Structured Prediction
Hal Daumé III, John Langford, Daniel Marcu
Machine learning Journal | July 2009, (2009)
Publications by Research Area
-
PRISE: Learning Temporal Action Abstractions as a Sequence Compression Problem
Ruijie Zheng, Ching-An Cheng, Hal Daumé III, Furong Huang, Andrey Kolobov
ICML 2024 | February 2024
PRISE: Learning Temporal Action Abstractions as a Sequence Compression Problem
Ruijie Zheng, Ching-An Cheng, Hal Daumé III, Furong Huang, Andrey Kolobov
ICML 2024 | February 2024
Premier-TACO is a Few-Shot Policy Learner: Pretraining Multitask Representation via Temporal Action-Driven Contrastive Loss
Ruijie Zheng, Yongyuan Liang, Xiyao Wang, Shuang Ma, Hal Daumé III, Huazhe Xu, John Langford, Praveen Palanisamy, Kalyan Shankar Basu, Furong Huang
ICML 2024 | February 2024
Define, Evaluate, and Improve Task-Oriented Cognitive Capabilities for Instruction Generation Models
Lingjun Zhao, Khanh Nguyen, Hal Daumé III
ACL 2023 | May 2023
A Framework for Learning to Request Rich and Contextually Useful Information from Humans
Khanh Nguyen, Yonatan Bisk, Hal Daumé III
ICML 2022 | July 2022
Promoting Fairness in Learned Models by Learning to Active Learn under Parity Constraints
Amr Sharaf, Hal Daumé III, Renkun Ni
FAccT 2022 | June 2022
Datasheets for Datasets
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III, Kate Crawford
Communications of the ACM | December 2021, Vol 64(12): pp. 86-92
From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence
David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna Wallach, Jennifer Wortman Vaughan
HCOMP 2021 | September 2021
Responsible computing during COVID-19 and beyond
Solon Barocas, Asia J. Biega, Margarita Boyarskaya, Kate Crawford, Hal Daumé III, Miro Dudík, Benjamin Fish, Mary L. Gray, Brent Hecht, Alexandra Olteanu, Forough Poursabzi-Sangdeh, Luke Stark, Jennifer Wortman Vaughan, Hanna Wallach, Marion Zepf
Communications of the ACM | July 2021, Vol 67(7): pp. 30-32
https://doi.org/10.1145/3466612
Operationalizing the Legal Principle of Data Minimization for Personalization
Asia J. Biega, Peter Potash, Hal Daumé III, Fernando Diaz, Michèle Finck
SIGIR 2020 | July 2020
Language (Technology) is Power: A Critical Survey of “Bias” in NLP
Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna Wallach
ACL | June 2020
Active Imitation Learning With Noisy Guidance
Kianté Brantley, Amr Sharaf, Hal Daumé III
May 2020
Towards Automatic Generation Of Questions From Long Answers
Shlok Kumar Mishra, Pranav Goel, Abhishek Sharma, Abhyuday Jagannatha, David Jacobs, Hal Daumé III
April 2020
Meta-Learning For Few-Shot NMT Adaptation
Amr Sharaf, Hany Hassan Awadalla, Hal Daumé III
April 2020
Weight of Evidence as a Basis for Human-Oriented Explanations
David Alvarez-Melis, Hal Daumé III, Jennifer Wortman Vaughan, Hanna Wallach
Workshop on Human-Centric Machine Learning at the 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada. | October 2019
Improving fairness in machine learning systems: What do industry practitioners need?
Ken Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miro Dudík, Hanna Wallach
2019 ACM CHI Conference on Human Factors in Computing Systems | June 2019
Logarithmic Time One-Against-Some
Hal Daumé III, Nikos Karampatziakis, John Langford, Paul Mineiro
ICML 2017 | April 2019
Active Learning for Cost-Sensitive Classification
Akshay Krishnamurthy, Alekh Agarwal, Tzu-Kuo Huang, John Langford, Hal Daumé III
Journal of Machine Learning Research | April 2019
Contextual Memory Trees
Wen Sun, Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro
February 2019
Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback
Chicheng Zhang, Alekh Agarwal, Hal Daumé III, John Langford, Sahand N Negahban
January 2019
Hierarchical Imitation and Reinforcement Learning
Hoang M Le, Nan Jiang, Alekh Agarwal, Miro Dudík, Yisong Yue, Hal Daumé III
International Conference on Machine Learning (ICML) | July 2018
International Conference on Machine Learning
A Credit Assignment Compiler for Joint Prediction
Kai-Wei Chang, He He, Hal Daumé III, John Langford, Stephane Ross
June 2016
Learning to Search Better Than Your Teacher
Kai-Wei Chang, Akshay Krishnamurthy, Alekh Agarwal, Hal Daumé III, John Langford
International Conference on Machine Learning | July 2015
International Conference on Machine Learning
Learning to Search Better than Your Teacher
Kai-Wei Chang, Akshay Krishnamurthy, Alekh Agarwal, John Langford, Hal Daumé III
International Conference on Machine Learning | July 2015
Learning to Search for Dependencies
Kai-Wei Chang, He He, Hal Daumé III, John Langford
May 2015
Learning Reductions that Really Work
Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro
February 2015
Search-based Structured Prediction
Hal Daumé III, John Langford, Daniel Marcu
Machine learning Journal | July 2009, (2009)
-
Define, Evaluate, and Improve Task-Oriented Cognitive Capabilities for Instruction Generation Models
Lingjun Zhao, Khanh Nguyen, Hal Daumé III
ACL 2023 | May 2023
Responsible computing during COVID-19 and beyond
Solon Barocas, Asia J. Biega, Margarita Boyarskaya, Kate Crawford, Hal Daumé III, Miro Dudík, Benjamin Fish, Mary L. Gray, Brent Hecht, Alexandra Olteanu, Forough Poursabzi-Sangdeh, Luke Stark, Jennifer Wortman Vaughan, Hanna Wallach, Marion Zepf
Communications of the ACM | July 2021, Vol 67(7): pp. 30-32
https://doi.org/10.1145/3466612
Improving fairness in machine learning systems: What do industry practitioners need?
Ken Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miro Dudík, Hanna Wallach
2019 ACM CHI Conference on Human Factors in Computing Systems | June 2019
-
Deconstructing NLG Evaluation: Evaluation Practices, Assumptions, and Their Implications
Kaitlyn Zhou, Su Lin Blodgett, Adam Trischler, Hal Daumé III, Kaheer Suleman, Alexandra Olteanu
NAACL 2022 | May 2022
Distantly-Supervised Evidence Retrieval Enables Question Answering without Evidence Annotation
Chen Zhao, Chenyan Xiong, Jordan Boyd-Graber, Hal Daumé III
2021 Empirical Methods in Natural Language Processing | October 2021
Language (Technology) is Power: A Critical Survey of “Bias” in NLP
Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna Wallach
ACL | June 2020
Active Imitation Learning With Noisy Guidance
Kianté Brantley, Amr Sharaf, Hal Daumé III
May 2020
Meta-Learning For Few-Shot NMT Adaptation
Amr Sharaf, Hany Hassan Awadalla, Hal Daumé III
April 2020
-
Responsible computing during COVID-19 and beyond
Solon Barocas, Asia J. Biega, Margarita Boyarskaya, Kate Crawford, Hal Daumé III, Miro Dudík, Benjamin Fish, Mary L. Gray, Brent Hecht, Alexandra Olteanu, Forough Poursabzi-Sangdeh, Luke Stark, Jennifer Wortman Vaughan, Hanna Wallach, Marion Zepf
Communications of the ACM | July 2021, Vol 67(7): pp. 30-32
https://doi.org/10.1145/3466612
Operationalizing the Legal Principle of Data Minimization for Personalization
Asia J. Biega, Peter Potash, Hal Daumé III, Fernando Diaz, Michèle Finck
SIGIR 2020 | July 2020
Language (Technology) is Power: A Critical Survey of “Bias” in NLP
Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna Wallach
ACL | June 2020
-
Multi-Step Reasoning Over Unstructured Text with Beam Dense Retrieval
Chen Zhao, Chenyan Xiong, Jordan L. Boyd-Graber, Hal Daumé III
April 2021
-
Operationalizing the Legal Principle of Data Minimization for Personalization
Asia J. Biega, Peter Potash, Hal Daumé III, Fernando Diaz, Michèle Finck
SIGIR 2020 | July 2020
-
Operationalizing the Legal Principle of Data Minimization for Personalization
Asia J. Biega, Peter Potash, Hal Daumé III, Fernando Diaz, Michèle Finck
SIGIR 2020 | July 2020
Publications by Type
-
PRISE: Learning Temporal Action Abstractions as a Sequence Compression Problem
Ruijie Zheng, Ching-An Cheng, Hal Daumé III, Furong Huang, Andrey Kolobov
ICML 2024 | February 2024
PRISE: Learning Temporal Action Abstractions as a Sequence Compression Problem
Ruijie Zheng, Ching-An Cheng, Hal Daumé III, Furong Huang, Andrey Kolobov
ICML 2024 | February 2024
Premier-TACO is a Few-Shot Policy Learner: Pretraining Multitask Representation via Temporal Action-Driven Contrastive Loss
Ruijie Zheng, Yongyuan Liang, Xiyao Wang, Shuang Ma, Hal Daumé III, Huazhe Xu, John Langford, Praveen Palanisamy, Kalyan Shankar Basu, Furong Huang
ICML 2024 | February 2024
Define, Evaluate, and Improve Task-Oriented Cognitive Capabilities for Instruction Generation Models
Lingjun Zhao, Khanh Nguyen, Hal Daumé III
ACL 2023 | May 2023
A Framework for Learning to Request Rich and Contextually Useful Information from Humans
Khanh Nguyen, Yonatan Bisk, Hal Daumé III
ICML 2022 | July 2022
Promoting Fairness in Learned Models by Learning to Active Learn under Parity Constraints
Amr Sharaf, Hal Daumé III, Renkun Ni
FAccT 2022 | June 2022
Deconstructing NLG Evaluation: Evaluation Practices, Assumptions, and Their Implications
Kaitlyn Zhou, Su Lin Blodgett, Adam Trischler, Hal Daumé III, Kaheer Suleman, Alexandra Olteanu
NAACL 2022 | May 2022
Distantly-Supervised Evidence Retrieval Enables Question Answering without Evidence Annotation
Chen Zhao, Chenyan Xiong, Jordan Boyd-Graber, Hal Daumé III
2021 Empirical Methods in Natural Language Processing | October 2021
From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence
David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna Wallach, Jennifer Wortman Vaughan
HCOMP 2021 | September 2021
Operationalizing the Legal Principle of Data Minimization for Personalization
Asia J. Biega, Peter Potash, Hal Daumé III, Fernando Diaz, Michèle Finck
SIGIR 2020 | July 2020
Language (Technology) is Power: A Critical Survey of “Bias” in NLP
Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna Wallach
ACL | June 2020
Weight of Evidence as a Basis for Human-Oriented Explanations
David Alvarez-Melis, Hal Daumé III, Jennifer Wortman Vaughan, Hanna Wallach
Workshop on Human-Centric Machine Learning at the 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada. | October 2019
Improving fairness in machine learning systems: What do industry practitioners need?
Ken Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miro Dudík, Hanna Wallach
2019 ACM CHI Conference on Human Factors in Computing Systems | June 2019
Logarithmic Time One-Against-Some
Hal Daumé III, Nikos Karampatziakis, John Langford, Paul Mineiro
ICML 2017 | April 2019
Hierarchical Imitation and Reinforcement Learning
Hoang M Le, Nan Jiang, Alekh Agarwal, Miro Dudík, Yisong Yue, Hal Daumé III
International Conference on Machine Learning (ICML) | July 2018
International Conference on Machine Learning
Learning to Search Better Than Your Teacher
Kai-Wei Chang, Akshay Krishnamurthy, Alekh Agarwal, Hal Daumé III, John Langford
International Conference on Machine Learning | July 2015
International Conference on Machine Learning
Learning to Search Better than Your Teacher
Kai-Wei Chang, Akshay Krishnamurthy, Alekh Agarwal, John Langford, Hal Daumé III
International Conference on Machine Learning | July 2015
-
Datasheets for Datasets
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III, Kate Crawford
Communications of the ACM | December 2021, Vol 64(12): pp. 86-92
Responsible computing during COVID-19 and beyond
Solon Barocas, Asia J. Biega, Margarita Boyarskaya, Kate Crawford, Hal Daumé III, Miro Dudík, Benjamin Fish, Mary L. Gray, Brent Hecht, Alexandra Olteanu, Forough Poursabzi-Sangdeh, Luke Stark, Jennifer Wortman Vaughan, Hanna Wallach, Marion Zepf
Communications of the ACM | July 2021, Vol 67(7): pp. 30-32
https://doi.org/10.1145/3466612
Active Learning for Cost-Sensitive Classification
Akshay Krishnamurthy, Alekh Agarwal, Tzu-Kuo Huang, John Langford, Hal Daumé III
Journal of Machine Learning Research | April 2019
Search-based Structured Prediction
Hal Daumé III, John Langford, Daniel Marcu
Machine learning Journal | July 2009, (2009)
-
Multi-Step Reasoning Over Unstructured Text with Beam Dense Retrieval
Chen Zhao, Chenyan Xiong, Jordan L. Boyd-Graber, Hal Daumé III
April 2021
Active Imitation Learning With Noisy Guidance
Kianté Brantley, Amr Sharaf, Hal Daumé III
May 2020
Towards Automatic Generation Of Questions From Long Answers
Shlok Kumar Mishra, Pranav Goel, Abhishek Sharma, Abhyuday Jagannatha, David Jacobs, Hal Daumé III
April 2020
Meta-Learning For Few-Shot NMT Adaptation
Amr Sharaf, Hany Hassan Awadalla, Hal Daumé III
April 2020
Contextual Memory Trees
Wen Sun, Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro
February 2019
Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback
Chicheng Zhang, Alekh Agarwal, Hal Daumé III, John Langford, Sahand N Negahban
January 2019
A Credit Assignment Compiler for Joint Prediction
Kai-Wei Chang, He He, Hal Daumé III, John Langford, Stephane Ross
June 2016
Learning to Search for Dependencies
Kai-Wei Chang, He He, Hal Daumé III, John Langford
May 2015
Learning Reductions that Really Work
Alina Beygelzimer, Hal Daumé III, John Langford, Paul Mineiro
February 2015