Hanna Wallach

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Jennifer Wortman VaughanSenior Principal Researcher, Microsoft Research, New York CityAdresse e-mail validée de microsoft.com
Hal Daumé IIIAssociate Professor of Computer Science, University of MarylandAdresse e-mail validée de umiacs.umd.edu
David MimnoAssociate Professor, Cornell UniversityAdresse e-mail validée de cornell.edu
Solon BarocasPrincipal Researcher, Microsoft Research; Adjunct Associate Professor, Information Science, CornellAdresse e-mail validée de cornell.edu
Andrew McCallumDistinguished Professor of Computer Science, University of Massachusetts AmherstAdresse e-mail validée de cs.umass.edu
Su Lin BlodgettMicrosoft Research MontréalAdresse e-mail validée de microsoft.com
Miroslav DudikMicrosoft ResearchAdresse e-mail validée de microsoft.com
Aaron ScheinAssistant Professor of Statistics & Data Science at the University of ChicagoAdresse e-mail validée de uchicago.edu
Briana VecchioneCornell UniversityAdresse e-mail validée de cornell.edu
Jamie MorgensternUniversity of WashingtonAdresse e-mail validée de cs.washington.edu
Michael A. MadaioGoogle ResearchAdresse e-mail validée de google.com
David BleiProfessor of Statistics and Computer Science, Columbia UniversityAdresse e-mail validée de columbia.edu
Edmund M TalleyNational Institutes of HealthAdresse e-mail validée de nih.gov
Bruce A. DesmaraisProfessor, Department of Political Science, Penn State UniversityAdresse e-mail validée de psu.edu
Ryan CotterellETH ZürichAdresse e-mail validée de inf.ethz.ch
Sarah BirdMicrosoftAdresse e-mail validée de microsoft.com
Alekh AgarwalGoogleAdresse e-mail validée de google.com
Mingyuan ZhouAssociate Professor, University of Texas at AustinAdresse e-mail validée de mccombs.utexas.edu
Ming YinPurdue UniversityAdresse e-mail validée de purdue.edu
Kenneth HolsteinCarnegie Mellon UniversityAdresse e-mail validée de cs.cmu.edu

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Hanna Wallach

Partner Research Manager, Microsoft Research

Adresse e-mail validée de dirichlet.net - Page d'accueil

Fairness Interpretability Computational Social Science Machine Learning Natural Language Processing


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Optimizing semantic coherence in topic models D Mimno, H Wallach, E Talley, M Leenders, A McCallum Proceedings of the 2011 conference on empirical methods in natural language …, 2011	2623	2011
Datasheets for datasets T Gebru, J Morgenstern, B Vecchione, JW Vaughan, H Wallach, HD Iii, ... Communications of the ACM 64 (12), 86-92, 2021	2440	2021
Topic modeling: beyond bag-of-words HM Wallach Proceedings of the 23rd international conference on Machine learning, 977-984, 2006	1702	2006
Advances in neural information processing systems 31 S Bengio, HM Wallach, H Larochelle, K Grauman, N Cesa‐Bianchi, ... Annual conference on neural information processing systems 2018, NeurIPS …, 2018	1422*	2018
Evaluation methods for topic models HM Wallach, I Murray, R Salakhutdinov, D Mimno Proceedings of the 26th annual international conference on machine learning …, 2009	1279	2009
A reductions approach to fair classification A Agarwal, A Beygelzimer, M Dudík, J Langford, H Wallach International conference on machine learning, 60-69, 2018	1238	2018
Language (Technology) is Power: A Critical Survey of "Bias" in NLP SL Blodgett, S Barocas, H Daumé III, H Wallach arXiv preprint arXiv:2005.14050, 2020	1205	2020
Rethinking LDA: Why priors matter H Wallach, D Mimno, A McCallum Advances in neural information processing systems 22, 2009	1012	2009
Improving fairness in machine learning systems: What do industry practitioners need? K Holstein, J Wortman Vaughan, H Daumé III, M Dudik, H Wallach Proceedings of the 2019 CHI conference on human factors in computing systems …, 2019	875	2019
Manipulating and measuring model interpretability F Poursabzi-Sangdeh, DG Goldstein, JM Hofman, JW Wortman Vaughan, ... Proceedings of the 2021 CHI conference on human factors in computing systems …, 2021	836	2021
Conditional random fields: An introduction HM Wallach Technical reports (CIS) 22, 2-6, 2004	616	2004
Interpreting interpretability: understanding data scientists' use of interpretability tools for machine learning H Kaur, H Nori, S Jenkins, R Caruana, H Wallach, J Wortman Vaughan Proceedings of the 2020 CHI conference on human factors in computing systems …, 2020	577	2020
Understanding the effect of accuracy on trust in machine learning models M Yin, J Wortman Vaughan, H Wallach Proceedings of the 2019 chi conference on human factors in computing systems …, 2019	563	2019
Polylingual topic models D Mimno, H Wallach, J Naradowsky, DA Smith, A McCallum Proceedings of the 2009 conference on empirical methods in natural language …, 2009	484	2009
Bias in bios: A case study of semantic representation bias in a high-stakes setting M De-Arteaga, A Romanov, H Wallach, J Chayes, C Borgs, ... proceedings of the Conference on Fairness, Accountability, and Transparency …, 2019	478	2019
Co-designing checklists to understand organizational challenges and opportunities around fairness in AI MA Madaio, L Stark, J Wortman Vaughan, H Wallach Proceedings of the 2020 CHI conference on human factors in computing systems …, 2020	447	2020
Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, 8-14 December 2019, Vancouver, BC, Canada, 2019 HM Wallach, H Larochelle, A Beygelzimer, F d’Alché-Buc, EB Fox, ... URL http://papers. nips. cc/book/advances-in-neural-information-processing …, 2019	446*	2019
Fairlearn: A toolkit for assessing and improving fairness in AI S Bird, M Dudík, R Edgar, B Horn, R Lutz, V Milan, M Sameki, H Wallach, ... Microsoft, Tech. Rep. MSR-TR-2020-32, 2020	428	2020
Measurement and fairness AZ Jacobs, H Wallach Proceedings of the 2021 ACM conference on fairness, accountability, and …, 2021	418	2021
Counterfactual data augmentation for mitigating gender stereotypes in languages with rich morphology R Zmigrod, SJ Mielke, H Wallach, R Cotterell arXiv preprint arXiv:1906.04571, 2019	307	2019

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