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Hanna M. Wallach
Person information

- affiliation: Microsoft Research, New York, NY, USA
- affiliation: University of Massachusetts Amherst, USA
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2020 – today
- 2023
- [c48]Daricia Wilkinson
, Kate Crawford
, Hanna M. Wallach
, Deborah Raji
, Bogdana Rakova
, Ranjit Singh
, Angelika Strohmayer
, Ethan Zuckerman
:
Accountability in Algorithmic Systems: From Principles to Practice. CHI Extended Abstracts 2023: 521:1-521:4 - [i32]Jared Katzman, Angelina Wang, Morgan Klaus Scheuerman, Su Lin Blodgett, Kristen Laird, Hanna M. Wallach, Solon Barocas:
Taxonomizing and Measuring Representational Harms: A Look at Image Tagging. CoRR abs/2305.01776 (2023) - 2022
- [j10]Michael Madaio, Lisa Egede, Hariharan Subramonyam, Jennifer Wortman Vaughan, Hanna M. Wallach:
Assessing the Fairness of AI Systems: AI Practitioners' Processes, Challenges, and Needs for Support. Proc. ACM Hum. Comput. Interact. 6(CSCW1): 52:1-52:26 (2022) - [j9]Amy Heger, Liz B. Marquis, Mihaela Vorvoreanu, Hanna M. Wallach, Jennifer Wortman Vaughan:
Understanding Machine Learning Practitioners' Data Documentation Perceptions, Needs, Challenges, and Desiderata. Proc. ACM Hum. Comput. Interact. 6(CSCW2): 1-29 (2022) - [c47]Angelina Wang, Solon Barocas, Kristen Laird, Hanna M. Wallach:
Measuring Representational Harms in Image Captioning. FAccT 2022: 324-335 - [c46]Jessie J. Smith, Saleema Amershi, Solon Barocas, Hanna M. Wallach, Jennifer Wortman Vaughan:
REAL ML: Recognizing, Exploring, and Articulating Limitations of Machine Learning Research. FAccT 2022: 587-597 - [i31]Jessie J. Smith, Saleema Amershi, Solon Barocas, Hanna M. Wallach, Jennifer Wortman Vaughan:
REAL ML: Recognizing, Exploring, and Articulating Limitations of Machine Learning Research. CoRR abs/2205.08363 (2022) - [i30]Amy Heger, Elizabeth B. Marquis, Mihaela Vorvoreanu, Hanna M. Wallach, Jennifer Wortman Vaughan:
Understanding Machine Learning Practitioners' Data Documentation Perceptions, Needs, Challenges, and Desiderata. CoRR abs/2206.02923 (2022) - [i29]Angelina Wang, Solon Barocas, Kristen Laird, Hanna M. Wallach:
Measuring Representational Harms in Image Captioning. CoRR abs/2206.07173 (2022) - 2021
- [j8]Solon Barocas
, Asia J. Biega, Margarita Boyarskaya, Kate Crawford, Hal Daumé III, Miroslav Dudík, Benjamin Fish, Mary L. Gray, Brent J. Hecht, Alexandra Olteanu, Forough Poursabzi-Sangdeh, Luke Stark, Jennifer Wortman Vaughan, Hanna M. Wallach, Marion Zepf:
Responsible computing during COVID-19 and beyond. Commun. ACM 64(7): 30-32 (2021) - [j7]Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna M. Wallach, Hal Daumé III, Kate Crawford:
Datasheets for datasets. Commun. ACM 64(12): 86-92 (2021) - [j6]Alex Okeson, Rich Caruana, Nick Craswell, Kori Inkpen, Scott M. Lundberg, Harsha Nori, Hanna M. Wallach, Jennifer Wortman Vaughan:
Summarize with Caution: Comparing Global Feature Attributions. IEEE Data Eng. Bull. 44(4): 14-27 (2021) - [j5]Adina Williams, Lawrence Wolf-Sonkin, Damián E. Blasi, Hanna M. Wallach, Ryan Cotterell:
On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs. Trans. Assoc. Comput. Linguistics 9: 139-159 (2021) - [c45]Su Lin Blodgett, Gilsinia Lopez, Alexandra Olteanu, Robert Sim, Hanna M. Wallach:
Stereotyping Norwegian Salmon: An Inventory of Pitfalls in Fairness Benchmark Datasets. ACL/IJCNLP (1) 2021: 1004-1015 - [c44]Solon Barocas
, Anhong Guo, Ece Kamar, Jacquelyn Krones, Meredith Ringel Morris, Jennifer Wortman Vaughan, W. Duncan Wadsworth, Hanna M. Wallach:
Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs. AIES 2021: 368-378 - [c43]Forough Poursabzi-Sangdeh, Daniel G. Goldstein
, Jake M. Hofman, Jennifer Wortman Vaughan, Hanna M. Wallach:
Manipulating and Measuring Model Interpretability. CHI 2021: 237:1-237:52 - [c42]David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna M. Wallach, Jennifer Wortman Vaughan:
From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence. HCOMP 2021: 35-47 - [c41]Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna M. Wallach, Jennifer Wortman Vaughan:
Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning. DaSH@KDD 2021 - [c40]Aaron Schein, Anjali Nagulpally, Hanna M. Wallach, Patrick Flaherty:
Doubly non-central beta matrix factorization for DNA methylation data. UAI 2021: 1895-1904 - [i28]Solon Barocas, Anhong Guo, Ece Kamar, Jacquelyn Krones, Meredith Ringel Morris, Jennifer Wortman Vaughan, W. Duncan Wadsworth, Hanna M. Wallach:
Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs. CoRR abs/2103.06076 (2021) - [i27]David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna M. Wallach, Jennifer Wortman Vaughan:
A Human-Centered Interpretability Framework Based on Weight of Evidence. CoRR abs/2104.13299 (2021) - [i26]Aaron Schein, Anjali Nagulpally, Hanna M. Wallach, Patrick Flaherty:
Doubly Non-Central Beta Matrix Factorization for DNA Methylation Data. CoRR abs/2106.06691 (2021) - [i25]Michael Madaio, Lisa Egede, Hariharan Subramonyam, Jennifer Wortman Vaughan, Hanna M. Wallach:
Assessing the Fairness of AI Systems: AI Practitioners' Processes, Challenges, and Needs for Support. CoRR abs/2112.05675 (2021) - 2020
- [j4]Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna M. Wallach, Meredith Ringel Morris:
Toward fairness in AI for people with disabilities SBG@a research roadmap. ACM SIGACCESS Access. Comput. 125: 2 (2020) - [c39]Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna M. Wallach:
Language (Technology) is Power: A Critical Survey of "Bias" in NLP. ACL 2020: 5454-5476 - [c38]Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna M. Wallach, Jennifer Wortman Vaughan:
Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning. CHI 2020: 1-14 - [c37]Michael A. Madaio, Luke Stark, Jennifer Wortman Vaughan, Hanna M. Wallach:
Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI. CHI 2020: 1-14 - [c36]Kathy Baxter, Yoav Schlesinger, Sarah Aerni, Lewis Baker, Julie Dawson, Krishnaram Kenthapadi, Isabel M. Kloumann, Hanna M. Wallach:
Bridging the gap from AI ethics research to practice. FAT* 2020: 682 - [c35]Abigail Z. Jacobs, Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna M. Wallach:
The meaning and measurement of bias: lessons from natural language processing. FAT* 2020: 706 - [i24]Adina Williams, Ryan Cotterell, Lawrence Wolf-Sonkin, Damián E. Blasi, Hanna M. Wallach:
On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs. CoRR abs/2005.01204 (2020) - [i23]Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna M. Wallach:
Language (Technology) is Power: A Critical Survey of "Bias" in NLP. CoRR abs/2005.14050 (2020)
2010 – 2019
- 2019
- [c34]Ran Zmigrod, S. J. Mielke, Hanna M. Wallach, Ryan Cotterell:
Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology. ACL (1) 2019: 1651-1661 - [c33]Alexander Hoyle, Lawrence Wolf-Sonkin, Hanna M. Wallach, Isabelle Augenstein
, Ryan Cotterell:
Unsupervised Discovery of Gendered Language through Latent-Variable Modeling. ACL (1) 2019: 1706-1716 - [c32]Ming Yin, Jennifer Wortman Vaughan, Hanna M. Wallach:
Understanding the Effect of Accuracy on Trust in Machine Learning Models. CHI 2019: 279 - [c31]Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miroslav Dudík, Hanna M. Wallach:
Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need? CHI 2019: 600 - [c30]Adina Williams
, Damián E. Blasi, Lawrence Wolf-Sonkin, Hanna M. Wallach, Ryan Cotterell:
Quantifying the Semantic Core of Gender Systems. EMNLP/IJCNLP (1) 2019: 5733-5738 - [c29]Maria De-Arteaga, Alexey Romanov, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs
, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai:
Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting. FAT 2019: 120-128 - [c28]Aaron Schein, Zhiwei Steven Wu, Alexandra Schofield, Mingyuan Zhou, Hanna M. Wallach:
Locally Private Bayesian Inference for Count Models. ICML 2019: 5638-5648 - [c27]Alexander Hoyle, Lawrence Wolf-Sonkin, Hanna M. Wallach, Ryan Cotterell, Isabelle Augenstein
:
Combining Sentiment Lexica with a Multi-View Variational Autoencoder. NAACL-HLT (1) 2019: 635-640 - [c26]Alexey Romanov, Maria De-Arteaga, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Anna Rumshisky, Adam Kalai
:
What's in a Name? Reducing Bias in Bios without Access to Protected Attributes. NAACL-HLT (1) 2019: 4187-4195 - [c25]Aaron Schein, Scott W. Linderman, Mingyuan Zhou, David M. Blei, Hanna M. Wallach:
Poisson-Randomized Gamma Dynamical Systems. NeurIPS 2019: 781-792 - [e4]Hanna M. Wallach, Hugo Larochelle, Alina Beygelzimer, Florence d'Alché-Buc, Emily B. Fox, Roman Garnett:
Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada. 2019 [contents] - [i22]Maria De-Arteaga, Alexey Romanov, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai:
Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting. CoRR abs/1901.09451 (2019) - [i21]Alexander Hoyle, Lawrence Wolf-Sonkin, Hanna M. Wallach, Ryan Cotterell, Isabelle Augenstein:
Combining Sentiment Lexica with a Multi-View Variational Autoencoder. CoRR abs/1904.02839 (2019) - [i20]Alexey Romanov, Maria De-Arteaga, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Anna Rumshisky, Adam Tauman Kalai:
What's in a Name? Reducing Bias in Bios without Access to Protected Attributes. CoRR abs/1904.05233 (2019) - [i19]Ran Zmigrod, Sabrina J. Mielke, Hanna M. Wallach, Ryan Cotterell:
Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology. CoRR abs/1906.04571 (2019) - [i18]Alexander Hoyle, Lawrence Wolf-Sonkin, Hanna M. Wallach, Isabelle Augenstein, Ryan Cotterell:
Unsupervised Discovery of Gendered Language through Latent-Variable Modeling. CoRR abs/1906.04760 (2019) - [i17]Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna M. Wallach, Meredith Ringel Morris:
Toward Fairness in AI for People with Disabilities: A Research Roadmap. CoRR abs/1907.02227 (2019) - [i16]Aaron Schein, Scott W. Linderman, Mingyuan Zhou, David M. Blei, Hanna M. Wallach:
Poisson-Randomized Gamma Dynamical Systems. CoRR abs/1910.12991 (2019) - [i15]Adina Williams, Ryan Cotterell, Lawrence Wolf-Sonkin, Damián E. Blasi, Hanna M. Wallach:
Quantifying the Semantic Core of Gender Systems. CoRR abs/1910.13497 (2019) - [i14]David Alvarez-Melis, Hal Daumé III, Jennifer Wortman Vaughan, Hanna M. Wallach:
Weight of Evidence as a Basis for Human-Oriented Explanations. CoRR abs/1910.13503 (2019) - [i13]Abigail Z. Jacobs, Hanna M. Wallach:
Measurement and Fairness. CoRR abs/1912.05511 (2019) - 2018
- [j3]Hanna M. Wallach:
Computational social science ≠ computer science + social data. Commun. ACM 61(3): 42-44 (2018) - [c24]Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík, John Langford, Hanna M. Wallach:
A Reductions Approach to Fair Classification. ICML 2018: 60-69 - [e3]Samy Bengio, Hanna M. Wallach, Hugo Larochelle, Kristen Grauman, Nicolò Cesa-Bianchi, Roman Garnett:
Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montréal, Canada. 2018 [contents] - [i12]Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake M. Hofman, Jennifer Wortman Vaughan, Hanna M. Wallach:
Manipulating and Measuring Model Interpretability. CoRR abs/1802.07810 (2018) - [i11]Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík, John Langford, Hanna M. Wallach:
A Reductions Approach to Fair Classification. CoRR abs/1803.02453 (2018) - [i10]Aaron Schein, Zhiwei Steven Wu, Mingyuan Zhou, Hanna M. Wallach:
Locally Private Bayesian Inference for Count Models. CoRR abs/1803.08471 (2018) - [i9]Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna M. Wallach, Hal Daumé III, Kate Crawford:
Datasheets for Datasets. CoRR abs/1803.09010 (2018) - [i8]Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miroslav Dudík, Hanna M. Wallach:
Improving fairness in machine learning systems: What do industry practitioners need? CoRR abs/1812.05239 (2018) - 2017
- [j2]Solon Barocas
, danah boyd
, Sorelle A. Friedler, Hanna M. Wallach:
Social and Technical Trade-Offs in Data Science. Big Data 5(2): 71-72 (2017) - [c23]Rishabh Mehrotra, Ashton Anderson, Fernando Diaz, Amit Sharma, Hanna M. Wallach, Emine Yilmaz:
Auditing Search Engines for Differential Satisfaction Across Demographics. WWW (Companion Volume) 2017: 626-633 - [e2]Dirk Hovy
, Shannon L. Spruit, Margaret Mitchell, Emily M. Bender, Michael Strube, Hanna M. Wallach:
Proceedings of the First ACL Workshop on Ethics in Natural Language Processing, EthNLP@EACL, Valencia, Spain, April 4, 2017. Association for Computational Linguistics 2017, ISBN 978-1-945626-47-0 [contents] - [e1]Isabelle Guyon, Ulrike von Luxburg, Samy Bengio, Hanna M. Wallach, Rob Fergus, S. V. N. Vishwanathan, Roman Garnett:
Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA. 2017 [contents] - [i7]Aaron Schein, Mingyuan Zhou, Hanna M. Wallach:
Poisson-Gamma Dynamical Systems. CoRR abs/1701.05573 (2017) - [i6]Rishabh Mehrotra, Ashton Anderson, Fernando Diaz, Amit Sharma, Hanna M. Wallach, Emine Yilmaz:
Auditing Search Engines for Differential Satisfaction Across Demographics. CoRR abs/1705.10689 (2017) - 2016
- [c22]Abram Handler, Matthew Denny, Hanna M. Wallach, Brendan O'Connor:
Bag of What? Simple Noun Phrase Extraction for Text Analysis. NLP+CSS@EMNLP 2016: 114-124 - [c21]Allison June-Barlow Chaney, Hanna M. Wallach, Matthew Connelly, David M. Blei:
Detecting and Characterizing Events. EMNLP 2016: 1142-1152 - [c20]Aaron Schein, Mingyuan Zhou, David M. Blei, Hanna M. Wallach:
Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations. ICML 2016: 2810-2819 - [c19]Brenda Betancourt, Giacomo Zanella, Jeffrey W. Miller, Hanna M. Wallach, Abbas Zaidi, Beka Steorts:
Flexible Models for Microclustering with Application to Entity Resolution. NIPS 2016: 1417-1425 - [c18]Aaron Schein, Hanna M. Wallach, Mingyuan Zhou:
Poisson-Gamma dynamical systems. NIPS 2016: 5006-5014 - [c17]Rahul Goel, Sandeep Soni, Naman Goyal, John Paparrizos, Hanna M. Wallach, Fernando Diaz, Jacob Eisenstein:
The Social Dynamics of Language Change in Online Networks. SocInfo (1) 2016: 41-57 - [p1]Hanna M. Wallach:
Conclusion - Computational Social Science: Toward a Collaborative Future. Computational Social Science 2016: 307-316 - [i5]Aaron Schein, Mingyuan Zhou, David M. Blei, Hanna M. Wallach:
Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations. CoRR abs/1606.01855 (2016) - [i4]Rahul Goel, Sandeep Soni, Naman Goyal, John Paparrizos, Hanna M. Wallach, Fernando Diaz, Jacob Eisenstein:
The Social Dynamics of Language Change in Online Networks. CoRR abs/1609.02075 (2016) - 2015
- [c16]Fangjian Guo, Charles Blundell, Hanna M. Wallach, Katherine A. Heller:
The Bayesian Echo Chamber: Modeling Social Influence via Linguistic Accommodation. AISTATS 2015 - [c15]Aaron Schein, John W. Paisley, David M. Blei, Hanna M. Wallach:
Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts. KDD 2015: 1045-1054 - [i3]Aaron Schein, John W. Paisley, David M. Blei, Hanna M. Wallach:
Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts. CoRR abs/1506.03493 (2015) - 2014
- [j1]Winter A. Mason, Jennifer Wortman Vaughan, Hanna M. Wallach:
Computational social science and social computing. Mach. Learn. 95(3): 257-260 (2014) - [c14]Scott Counts, Munmun De Choudhury, Jana Diesner, Eric Gilbert, Marta C. González, Brian Keegan, Mor Naaman, Hanna M. Wallach:
Computational social science: CSCW in the social media era. CSCW Companion 2014: 105-108 - [i2]Fangjian Guo, Charles Blundell, Hanna M. Wallach, Katherine A. Heller:
The Bayesian Echo Chamber: Modeling Influence in Conversations. CoRR abs/1411.2674 (2014) - 2013
- [c13]Kriste Krstovski, David A. Smith, Hanna M. Wallach, Andrew McGregor:
Efficient Nearest-Neighbor Search in the Probability Simplex. ICTIR 2013: 22 - [i1]Aaron Schein, Juston Moore, Hanna M. Wallach:
Inferring Multilateral Relations from Dynamic Pairwise Interactions. CoRR abs/1311.3982 (2013) - 2012
- [c12]Anton Bakalov, Andrew McCallum, Hanna M. Wallach, David M. Mimno
:
Topic models for taxonomies. JCDL 2012: 237-240 - [c11]Peter M. Krafft, Juston Moore, Bruce A. Desmarais, Hanna M. Wallach:
Topic-Partitioned Multinetwork Embeddings. NIPS 2012: 2816-2824 - 2011
- [c10]David M. Mimno, Hanna M. Wallach, Edmund M. Talley, Miriam Leenders, Andrew McCallum:
Optimizing Semantic Coherence in Topic Models. EMNLP 2011: 262-272 - 2010
- [c9]Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghahramani:
Learning the Structure of Deep Sparse Graphical Models. AISTATS 2010: 1-8 - [c8]Hanna M. Wallach, Shane T. Jensen, Lee H. Dicker, Katherine A. Heller:
An Alternative Prior Process for Nonparametric Bayesian Clustering. AISTATS 2010: 892-899
2000 – 2009
- 2009
- [c7]David M. Mimno, Hanna M. Wallach, Jason Naradowsky, David A. Smith, Andrew McCallum:
Polylingual Topic Models. EMNLP 2009: 880-889 - [c6]Hanna M. Wallach, Iain Murray, Ruslan Salakhutdinov, David M. Mimno
:
Evaluation methods for topic models. ICML 2009: 1105-1112 - [c5]Hanna M. Wallach, David M. Mimno, Andrew McCallum:
Rethinking LDA: Why Priors Matter. NIPS 2009: 1973-1981 - 2008
- [c4]Mark Dredze, Hanna M. Wallach, Danny Puller, Tova Brooks, Josh Carroll, Joshua Magarick, John Blitzer, Fernando Pereira:
Intelligent Email: Aiding Users with AI. AAAI 2008: 1524-1527 - [c3]Mark Dredze
, Hanna M. Wallach, Danny Puller, Fernando Pereira:
Generating summary keywords for emails using topics. IUI 2008: 199-206 - 2006
- [c2]Hanna M. Wallach:
Topic modeling: beyond bag-of-words. ICML 2006: 977-984 - 2002
- [c1]Alan F. Blackwell, Hanna M. Wallach:
Diagrammatic Integration of Abstract Operations into Software Work Contexts. Diagrams 2002: 191-205
Coauthor Index

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