Hanna M. Wallach

117 papers A* 20A 5B 1C 2Misc 1Journal 57Unranked 28

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Comparison requires valid measurement: Rethinking attack success rate comparisons in AI red teaming. CoRR Alexandra Chouldechova, A. Feder Cooper, Solon Barocas, Abhinav Palia, Dan Vann, Hanna M. Wallach
2025	—	`conf`	Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge. ICML (Position Papers) Hanna M. Wallach, Meera A. Desai, A. Feder Cooper, Angelina Wang, Chad Atalla, Solon Barocas, Su Lin Blodgett, Alexandra Chouldechova, Emily Corvi, P. Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Nicholas J. Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
2025	J	`jnl`	Position: Evaluating Generative AI Systems is a Social Science Measurement Challenge. CoRR Hanna M. Wallach, Meera A. Desai, A. Feder Cooper, Angelina Wang, Chad Atalla, Solon Barocas, Su Lin Blodgett, Alexandra Chouldechova, Emily Corvi, P. Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Nicholas Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
2025	—	`conf`	Taxonomizing Representational Harms using Speech Act Theory. ACL (Findings) Emily Corvi, Hannah Washington, Stefanie Reed, Chad Atalla, Alexandra Chouldechova, P. Alex Dow, Jean Garcia-Gathright, Nicholas J. Pangakis, Emily Sheng, Dan Vann, Matthew Vogel, Hanna M. Wallach
2025	J	`jnl`	Taxonomizing Representational Harms using Speech Act Theory. CoRR Emily Corvi, Hannah Washington, Stefanie Reed, Chad Atalla, Alexandra Chouldechova, P. Alex Dow, Jean Garcia-Gathright, Nicholas Pangakis, Emily Sheng, Dan Vann, Matthew Vogel, Hanna M. Wallach
2025	J	`jnl`	Toward an Evaluation Science for Generative AI Systems. CoRR Laura Weidinger, Inioluwa Deborah Raji, Hanna M. Wallach, Margaret Mitchell, Angelina Wang, Olawale Salaudeen, Rishi Bommasani, Deep Ganguli, Sanmi Koyejo, William Isaac
2025	—	`conf`	Understanding and Meeting Practitioner Needs When Measuring Representational Harms Caused by LLM-Based Systems. ACL (Findings) Emma Harvey, Emily Sheng, Su Lin Blodgett, Alexandra Chouldechova, Jean Garcia-Gathright, Alexandra Olteanu, Hanna M. Wallach
2025	J	`jnl`	Understanding and Meeting Practitioner Needs When Measuring Representational Harms Caused by LLM-Based Systems. CoRR Emma Harvey, Emily Sheng, Su Lin Blodgett, Alexandra Chouldechova, Jean Garcia-Gathright, Alexandra Olteanu, Hanna M. Wallach
2025	J	`jnl`	Validating LLM-as-a-Judge Systems in the Absence of Gold Labels. CoRR Luke Guerdan, Solon Barocas, Kenneth Holstein, Hanna M. Wallach, Zhiwei Steven Wu, Alexandra Chouldechova
2024	—	`conf`	"One-Size-Fits-All"? Examining Expectations around What Constitute "Fair" or "Good" NLG System Behaviors. NAACL-HLT Li Lucy, Su Lin Blodgett, Milad Shokouhi, Hanna M. Wallach, Alexandra Olteanu
2024	J	`jnl`	A Framework for Evaluating LLMs Under Task Indeterminacy. CoRR Luke Guerdan, Hanna M. Wallach, Solon Barocas, Alexandra Chouldechova
2024	J	`jnl`	A Shared Standard for Valid Measurement of Generative AI Systems' Capabilities, Risks, and Impacts. CoRR Alexandra Chouldechova, Chad Atalla, Solon Barocas, A. Feder Cooper, Emily Corvi, P. Alex Dow, Jean Garcia-Gathright, Nicholas Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Matthew Vogel, Hannah Washington, Hanna M. Wallach
2024	J	`jnl`	Dimensions of Generative AI Evaluation Design. CoRR P. Alex Dow, Jennifer Wortman Vaughan, Solon Barocas, Chad Atalla, Alexandra Chouldechova, Hanna M. Wallach
2024	J	`jnl`	Evaluating Generative AI Systems is a Social Science Measurement Challenge. CoRR Hanna M. Wallach, Meera A. Desai, Nicholas Pangakis, A. Feder Cooper, Angelina Wang, Solon Barocas, Alexandra Chouldechova, Chad Atalla, Su Lin Blodgett, Emily Corvi, P. Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
2024	J	`jnl`	Gaps Between Research and Practice When Measuring Representational Harms Caused by LLM-Based Systems. CoRR Emma Harvey, Emily Sheng, Su Lin Blodgett, Alexandra Chouldechova, Jean Garcia-Gathright, Alexandra Olteanu, Hanna M. Wallach
2024	J	`jnl`	Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy, Research, and Practice. CoRR A. Feder Cooper, Christopher A. Choquette-Choo, Miranda Bogen, Matthew Jagielski, Katja Filippova, Ken Ziyu Liu, Alexandra Chouldechova, Jamie Hayes, Yangsibo Huang, Niloofar Mireshghallah, Ilia Shumailov, Eleni Triantafillou, Peter Kairouz, Nicole Mitchell, Percy Liang, Daniel E. Ho, Yejin Choi, Sanmi Koyejo, Fernando A. Delgado, James Grimmelmann, Vitaly Shmatikov, Christopher De Sa, Solon Barocas, Amy Cyphert, Mark A. Lemley, danah boyd, Jennifer Wortman Vaughan, Miles Brundage, David Bau, Seth Neel, Abigail Z. Jacobs, Andreas Terzis, Hanna M. Wallach, Nicolas Papernot, Katherine Lee
2024	J	`jnl`	Tinker, Tailor, Configure, Customize: The Articulation Work of Contextualizing an AI Fairness Checklist. Proc. ACM Hum. Comput. Interact. Michael A. Madaio, Jingya Chen, Hanna M. Wallach, Jennifer Wortman Vaughan
2024	—	`conf`	Understanding the Impacts of Language Technologies' Performance Disparities on African American Language Speakers. ACL (Findings) Jay Cunningham, Su Lin Blodgett, Michael Madaio, Hal Daumé III, Christina N. Harrington, Hanna M. Wallach
2023	J	`jnl`	"One-size-fits-all"? Observations and Expectations of NLG Systems Across Identity-Related Language Features. CoRR Li Lucy, Su Lin Blodgett, Milad Shokouhi, Hanna M. Wallach, Alexandra Olteanu
2023	J	`jnl`	A Framework for Automated Measurement of Responsible AI Harms in Generative AI Applications. CoRR Ahmed Magooda, Alec Helyar, Kyle Jackson, David Sullivan, Chad Atalla, Emily Sheng, Dan Vann, Richard Edgar, Hamid Palangi, Roman Lutz, Hongliang Kong, Vincent Yun, Eslam Kamal, Federico Zarfati, Hanna M. Wallach, Sarah Bird, Mei Chen
2023	—	`conf`	Accountability in Algorithmic Systems: From Principles to Practice. CHI Extended Abstracts Daricia Wilkinson, Kate Crawford, Hanna M. Wallach, Inioluwa Deborah Raji, Bogdana Rakova, Ranjit Singh, Angelika Strohmayer, Ethan Zuckerman
2023	—	`conf`	FairPrism: Evaluating Fairness-Related Harms in Text Generation. ACL (1) Eve Fleisig, Aubrie Amstutz, Chad Atalla, Su Lin Blodgett, Hal Daumé III, Alexandra Olteanu, Emily Sheng, Dan Vann, Hanna M. Wallach
2023	A*	`conf`	Taxonomizing and Measuring Representational Harms: A Look at Image Tagging. AAAI Jared Katzman, Angelina Wang, Morgan Klaus Scheuerman, Su Lin Blodgett, Kristen Laird, Hanna M. Wallach, Solon Barocas
2023	J	`jnl`	Taxonomizing and Measuring Representational Harms: A Look at Image Tagging. CoRR Jared Katzman, Angelina Wang, Morgan Klaus Scheuerman, Su Lin Blodgett, Kristen Laird, Hanna M. Wallach, Solon Barocas
2022	J	`jnl`	Assessing the Fairness of AI Systems: AI Practitioners' Processes, Challenges, and Needs for Support. Proc. ACM Hum. Comput. Interact. Michael Madaio, Lisa Egede, Hariharan Subramonyam, Jennifer Wortman Vaughan, Hanna M. Wallach
2022	—	`conf`	Measuring Representational Harms in Image Captioning. FAccT Angelina Wang, Solon Barocas, Kristen Laird, Hanna M. Wallach
2022	J	`jnl`	Measuring Representational Harms in Image Captioning. CoRR Angelina Wang, Solon Barocas, Kristen Laird, Hanna M. Wallach
2022	—	`conf`	REAL ML: Recognizing, Exploring, and Articulating Limitations of Machine Learning Research. FAccT Jessie J. Smith, Saleema Amershi, Solon Barocas, Hanna M. Wallach, Jennifer Wortman Vaughan
2022	J	`jnl`	REAL ML: Recognizing, Exploring, and Articulating Limitations of Machine Learning Research. CoRR Jessie J. Smith, Saleema Amershi, Solon Barocas, Hanna M. Wallach, Jennifer Wortman Vaughan
2022	J	`jnl`	Understanding Machine Learning Practitioners' Data Documentation Perceptions, Needs, Challenges, and Desiderata. CoRR Amy Heger, Elizabeth B. Marquis, Mihaela Vorvoreanu, Hanna M. Wallach, Jennifer Wortman Vaughan
2022	J	`jnl`	Understanding Machine Learning Practitioners' Data Documentation Perceptions, Needs, Challenges, and Desiderata. Proc. ACM Hum. Comput. Interact. Amy Heger, Liz B. Marquis, Mihaela Vorvoreanu, Hanna M. Wallach, Jennifer Wortman Vaughan
2021	J	`jnl`	A Human-Centered Interpretability Framework Based on Weight of Evidence. CoRR David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna M. Wallach, Jennifer Wortman Vaughan
2021	J	`jnl`	Assessing the Fairness of AI Systems: AI Practitioners' Processes, Challenges, and Needs for Support. CoRR Michael Madaio, Lisa Egede, Hariharan Subramonyam, Jennifer Wortman Vaughan, Hanna M. Wallach
2021	J	`jnl`	Datasheets for datasets. Commun. ACM Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna M. Wallach, Hal Daumé III, Kate Crawford
2021	C	`conf`	Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs. AIES Solon Barocas, Anhong Guo, Ece Kamar, Jacquelyn Krones, Meredith Ringel Morris, Jennifer Wortman Vaughan, W. Duncan Wadsworth, Hanna M. Wallach
2021	J	`jnl`	Designing Disaggregated Evaluations of AI Systems: Choices, Considerations, and Tradeoffs. CoRR Solon Barocas, Anhong Guo, Ece Kamar, Jacquelyn Krones, Meredith Ringel Morris, Jennifer Wortman Vaughan, W. Duncan Wadsworth, Hanna M. Wallach
2021	J	`jnl`	Doubly Non-Central Beta Matrix Factorization for DNA Methylation Data. CoRR Aaron Schein, Anjali Nagulpally, Hanna M. Wallach, Patrick Flaherty
2021	A	`conf`	Doubly non-central beta matrix factorization for DNA methylation data. UAI Aaron Schein, Anjali Nagulpally, Hanna M. Wallach, Patrick Flaherty
2021	B	`conf`	From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence. HCOMP David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna M. Wallach, Jennifer Wortman Vaughan
2021	—	`conf`	Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning. DaSH@KDD Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna M. Wallach, Jennifer Wortman Vaughan
2021	A*	`conf`	Manipulating and Measuring Model Interpretability. CHI Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake M. Hofman, Jennifer Wortman Vaughan, Hanna M. Wallach
2021	J	`jnl`	On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs. Trans. Assoc. Comput. Linguistics Adina Williams, Lawrence Wolf-Sonkin, Damián E. Blasi, Hanna M. Wallach, Ryan Cotterell
2021	J	`jnl`	Responsible computing during COVID-19 and beyond. Commun. ACM 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
2021	—	`conf`	Stereotyping Norwegian Salmon: An Inventory of Pitfalls in Fairness Benchmark Datasets. ACL/IJCNLP (1) Su Lin Blodgett, Gilsinia Lopez, Alexandra Olteanu, Robert Sim, Hanna M. Wallach
2021	J	`jnl`	Summarize with Caution: Comparing Global Feature Attributions. IEEE Data Eng. Bull. Alex Okeson, Rich Caruana, Nick Craswell, Kori Inkpen, Scott M. Lundberg, Harsha Nori, Hanna M. Wallach, Jennifer Wortman Vaughan
2020	—	`conf`	Bridging the gap from AI ethics research to practice. FAT* Kathy Baxter, Yoav Schlesinger, Sarah Aerni, Lewis J. Baker, Julie Dawson, Krishnaram Kenthapadi, Isabel M. Kloumann, Hanna M. Wallach
2020	A*	`conf`	Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI. CHI Michael A. Madaio, Luke Stark, Jennifer Wortman Vaughan, Hanna M. Wallach
2020	A*	`conf`	Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning. CHI Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna M. Wallach, Jennifer Wortman Vaughan
2020	A*	`conf`	Language (Technology) is Power: A Critical Survey of "Bias" in NLP. ACL Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna M. Wallach
2020	J	`jnl`	Language (Technology) is Power: A Critical Survey of "Bias" in NLP. CoRR Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna M. Wallach
2020	J	`jnl`	On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs. CoRR Adina Williams, Ryan Cotterell, Lawrence Wolf-Sonkin, Damián E. Blasi, Hanna M. Wallach
2020	—	`conf`	The meaning and measurement of bias: lessons from natural language processing. FAT* Abigail Z. Jacobs, Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna M. Wallach
2020	J	`jnl`	Toward fairness in AI for people with disabilities SBG@a research roadmap. ACM SIGACCESS Access. Comput. Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna M. Wallach, Meredith Ringel Morris
2019	A*	`ed.`	Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada. NeurIPS Hanna M. Wallach, Hugo Larochelle, Alina Beygelzimer, Florence d'Alché-Buc, Emily B. Fox, Roman Garnett
2019	—	`conf`	Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting. FAT Maria De-Arteaga, Alexey Romanov, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai
2019	J	`jnl`	Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting. CoRR Maria De-Arteaga, Alexey Romanov, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai
2019	—	`conf`	Combining Sentiment Lexica with a Multi-View Variational Autoencoder. NAACL-HLT (1) Alexander Miserlis Hoyle, Lawrence Wolf-Sonkin, Hanna M. Wallach, Ryan Cotterell, Isabelle Augenstein
2019	J	`jnl`	Combining Sentiment Lexica with a Multi-View Variational Autoencoder. CoRR Alexander Miserlis Hoyle, Lawrence Wolf-Sonkin, Hanna M. Wallach, Ryan Cotterell, Isabelle Augenstein
2019	—	`conf`	Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology. ACL (1) Ran Zmigrod, S. J. Mielke, Hanna M. Wallach, Ryan Cotterell
2019	J	`jnl`	Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology. CoRR Ran Zmigrod, Sabrina J. Mielke, Hanna M. Wallach, Ryan Cotterell
2019	A*	`conf`	Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need? CHI Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miroslav Dudík, Hanna M. Wallach
2019	A*	`conf`	Locally Private Bayesian Inference for Count Models. ICML Aaron Schein, Zhiwei Steven Wu, Alexandra Schofield, Mingyuan Zhou, Hanna M. Wallach
2019	J	`jnl`	Measurement and Fairness. CoRR Abigail Z. Jacobs, Hanna M. Wallach
2019	A*	`conf`	Poisson-Randomized Gamma Dynamical Systems. NeurIPS Aaron Schein, Scott W. Linderman, Mingyuan Zhou, David M. Blei, Hanna M. Wallach
2019	J	`jnl`	Poisson-Randomized Gamma Dynamical Systems. CoRR Aaron Schein, Scott W. Linderman, Mingyuan Zhou, David M. Blei, Hanna M. Wallach
2019	—	`conf`	Quantifying the Semantic Core of Gender Systems. EMNLP/IJCNLP (1) Adina Williams, Damián E. Blasi, Lawrence Wolf-Sonkin, Hanna M. Wallach, Ryan Cotterell
2019	J	`jnl`	Quantifying the Semantic Core of Gender Systems. CoRR Adina Williams, Ryan Cotterell, Lawrence Wolf-Sonkin, Damián E. Blasi, Hanna M. Wallach
2019	J	`jnl`	Toward Fairness in AI for People with Disabilities: A Research Roadmap. CoRR Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna M. Wallach, Meredith Ringel Morris
2019	A*	`conf`	Understanding the Effect of Accuracy on Trust in Machine Learning Models. CHI Ming Yin, Jennifer Wortman Vaughan, Hanna M. Wallach
2019	—	`conf`	Unsupervised Discovery of Gendered Language through Latent-Variable Modeling. ACL (1) Alexander Miserlis Hoyle, Lawrence Wolf-Sonkin, Hanna M. Wallach, Isabelle Augenstein, Ryan Cotterell
2019	J	`jnl`	Unsupervised Discovery of Gendered Language through Latent-Variable Modeling. CoRR Alexander Miserlis Hoyle, Lawrence Wolf-Sonkin, Hanna M. Wallach, Isabelle Augenstein, Ryan Cotterell
2019	J	`jnl`	Weight of Evidence as a Basis for Human-Oriented Explanations. CoRR David Alvarez-Melis, Hal Daumé III, Jennifer Wortman Vaughan, Hanna M. Wallach
2019	—	`conf`	What's in a Name? Reducing Bias in Bios without Access to Protected Attributes. NAACL-HLT (1) Alexey Romanov, Maria De-Arteaga, Hanna M. Wallach, Jennifer T. Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Cem Geyik, Krishnaram Kenthapadi, Anna Rumshisky, Adam Kalai
2019	J	`jnl`	What's in a Name? Reducing Bias in Bios without Access to Protected Attributes. CoRR 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
2018	A*	`conf`	A Reductions Approach to Fair Classification. ICML Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík, John Langford, Hanna M. Wallach
2018	J	`jnl`	A Reductions Approach to Fair Classification. CoRR Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík, John Langford, Hanna M. Wallach
2018	A*	`ed.`	Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montréal, Canada. NeurIPS Samy Bengio, Hanna M. Wallach, Hugo Larochelle, Kristen Grauman, Nicolò Cesa-Bianchi, Roman Garnett
2018	J	`jnl`	Computational social science ≠ computer science + social data. Commun. ACM Hanna M. Wallach
2018	J	`jnl`	Datasheets for Datasets. CoRR Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna M. Wallach, Hal Daumé III, Kate Crawford
2018	J	`jnl`	Improving fairness in machine learning systems: What do industry practitioners need? CoRR Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miroslav Dudík, Hanna M. Wallach
2018	J	`jnl`	Locally Private Bayesian Inference for Count Models. CoRR Aaron Schein, Zhiwei Steven Wu, Mingyuan Zhou, Hanna M. Wallach
2018	J	`jnl`	Manipulating and Measuring Model Interpretability. CoRR Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake M. Hofman, Jennifer Wortman Vaughan, Hanna M. Wallach
2017	—	`ed.`	Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA Isabelle Guyon, Ulrike von Luxburg, Samy Bengio, Hanna M. Wallach, Rob Fergus, S. V. N. Vishwanathan, Roman Garnett
2017	—	`conf`	Auditing Search Engines for Differential Satisfaction Across Demographics. WWW (Companion Volume) Rishabh Mehrotra, Ashton Anderson, Fernando Diaz, Amit Sharma, Hanna M. Wallach, Emine Yilmaz
2017	J	`jnl`	Auditing Search Engines for Differential Satisfaction Across Demographics. CoRR Rishabh Mehrotra, Ashton Anderson, Fernando Diaz, Amit Sharma, Hanna M. Wallach, Emine Yilmaz
2017	J	`jnl`	Poisson-Gamma Dynamical Systems. CoRR Aaron Schein, Mingyuan Zhou, Hanna M. Wallach
2017	—	`ed.`	Proceedings of the First ACL Workshop on Ethics in Natural Language Processing, EthNLP@EACL, Valencia, Spain, April 4, 2017 EthNLP@EACL Dirk Hovy, Shannon L. Spruit, Margaret Mitchell, Emily M. Bender, Michael Strube, Hanna M. Wallach
2017	J	`jnl`	Social and Technical Trade-Offs in Data Science. Big Data Solon Barocas, danah boyd, Sorelle A. Friedler, Hanna M. Wallach
2016	—	`conf`	Bag of What? Simple Noun Phrase Extraction for Text Analysis. NLP+CSS@EMNLP Abram Handler, Matthew Denny, Hanna M. Wallach, Brendan O'Connor
2016	A*	`conf`	Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations. ICML Aaron Schein, Mingyuan Zhou, David M. Blei, Hanna M. Wallach
2016	J	`jnl`	Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations. CoRR Aaron Schein, Mingyuan Zhou, David M. Blei, Hanna M. Wallach
2016	—	`ch.`	Conclusion - Computational Social Science: Toward a Collaborative Future. Computational Social Science Hanna M. Wallach
2016	A*	`conf`	Detecting and Characterizing Events. EMNLP Allison June-Barlow Chaney, Hanna M. Wallach, Matthew Connelly, David M. Blei
2016	—	`conf`	Flexible Models for Microclustering with Application to Entity Resolution. NIPS Brenda Betancourt, Giacomo Zanella, Jeffrey W. Miller, Hanna M. Wallach, Abbas Zaidi, Beka Steorts
2016	—	`conf`	Poisson-Gamma dynamical systems. NIPS Aaron Schein, Hanna M. Wallach, Mingyuan Zhou
2016	—	`conf`	The Social Dynamics of Language Change in Online Networks. SocInfo (1) Rahul Goel, Sandeep Soni, Naman Goyal, John Paparrizos, Hanna M. Wallach, Fernando Diaz, Jacob Eisenstein
2016	J	`jnl`	The Social Dynamics of Language Change in Online Networks. CoRR Rahul Goel, Sandeep Soni, Naman Goyal, John Paparrizos, Hanna M. Wallach, Fernando Diaz, Jacob Eisenstein
2015	A*	`conf`	Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts. KDD Aaron Schein, John W. Paisley, David M. Blei, Hanna M. Wallach
2015	J	`jnl`	Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts. CoRR Aaron Schein, John W. Paisley, David M. Blei, Hanna M. Wallach
2015	A	`conf`	The Bayesian Echo Chamber: Modeling Social Influence via Linguistic Accommodation. AISTATS Fangjian Guo, Charles Blundell, Hanna M. Wallach, Katherine A. Heller
2014	J	`jnl`	Computational social science and social computing. Mach. Learn. Winter A. Mason, Jennifer Wortman Vaughan, Hanna M. Wallach
2014	—	`conf`	Computational social science: CSCW in the social media era. CSCW Companion Scott Counts, Munmun De Choudhury, Jana Diesner, Eric Gilbert, Marta C. González, Brian Keegan, Mor Naaman, Hanna M. Wallach
2014	J	`jnl`	The Bayesian Echo Chamber: Modeling Influence in Conversations. CoRR Fangjian Guo, Charles Blundell, Hanna M. Wallach, Katherine A. Heller
2013	Misc	`conf`	Efficient Nearest-Neighbor Search in the Probability Simplex. ICTIR Kriste Krstovski, David A. Smith, Hanna M. Wallach, Andrew McGregor
2013	J	`jnl`	Inferring Multilateral Relations from Dynamic Pairwise Interactions. CoRR Aaron Schein, Juston Moore, Hanna M. Wallach
2012	—	`conf`	Topic models for taxonomies. JCDL Anton Bakalov, Andrew McCallum, Hanna M. Wallach, David M. Mimno
2012	—	`conf`	Topic-Partitioned Multinetwork Embeddings. NIPS Peter M. Krafft, Juston Moore, Bruce A. Desmarais, Hanna M. Wallach
2011	A*	`conf`	Optimizing Semantic Coherence in Topic Models. EMNLP David M. Mimno, Hanna M. Wallach, Edmund M. Talley, Miriam Leenders, Andrew McCallum
2010	A	`conf`	An Alternative Prior Process for Nonparametric Bayesian Clustering. AISTATS Hanna M. Wallach, Shane T. Jensen, Lee H. Dicker, Katherine A. Heller
2010	A	`conf`	Learning the Structure of Deep Sparse Graphical Models. AISTATS Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghahramani
2009	A*	`conf`	Evaluation methods for topic models. ICML Hanna M. Wallach, Iain Murray, Ruslan Salakhutdinov, David M. Mimno
2009	A*	`conf`	Polylingual Topic Models. EMNLP David M. Mimno, Hanna M. Wallach, Jason Naradowsky, David A. Smith, Andrew McCallum
2009	—	`conf`	Rethinking LDA: Why Priors Matter. NIPS Hanna M. Wallach, David M. Mimno, Andrew McCallum
2008	A	`conf`	Generating summary keywords for emails using topics. IUI Mark Dredze, Hanna M. Wallach, Danny Puller, Fernando Pereira
2008	A*	`conf`	Intelligent Email: Aiding Users with AI. AAAI Mark Dredze, Hanna M. Wallach, Danny Puller, Tova Brooks, Josh Carroll, Joshua Magarick, John Blitzer, Fernando Pereira
2006	A*	`conf`	Topic modeling: beyond bag-of-words. ICML Hanna M. Wallach
2002	C	`conf`	Diagrammatic Integration of Abstract Operations into Software Work Contexts. Diagrams Alan F. Blackwell, Hanna M. Wallach