| 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 | 2081 | 2011 |
| Topic modeling: beyond bag-of-words HM Wallach Proceedings of the 23rd international conference on Machine learning, 977-984, 2006 | 1573 | 2006 |
| Datasheets for datasets T Gebru, J Morgenstern, B Vecchione, JW Vaughan, H Wallach, HD Iii, ... Communications of the ACM 64 (12), 86-92, 2021 | 1401 | 2021 |
| Evaluation methods for topic models HM Wallach, I Murray, R Salakhutdinov, D Mimno Proceedings of the 26th annual international conference on machine learning …, 2009 | 1128 | 2009 |
| Rethinking LDA: Why priors matter H Wallach, D Mimno, A McCallum Advances in neural information processing systems 22, 2009 | 911 | 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 | 854 | 2018 |
| 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 | 802* | 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 | 662 | 2020 |
| 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 | 596 | 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 | 575 | 2021 |
| Conditional random fields: An introduction HM Wallach Technical Reports (CIS), 22, 2004 | 570 | 2004 |
| 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 | 455 | 2009 |
| 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 | 341* | 2019 |
| 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 | 338 | 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 | 333 | 2019 |
| 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 | 289 | 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 | 271 | 2020 |
| Measurement and fairness AZ Jacobs, H Wallach Proceedings of the 2021 ACM conference on fairness, accountability, and …, 2021 | 255 | 2021 |
| Efficient training of conditional random fields H Wallach Master’s thesis, University of Edinburgh, 2002 | 234 | 2002 |
| Structured topic models for language HM Wallach University of Cambridge, 2008 | 223 | 2008 |
Jennifer Wortman VaughanSenior Principal Researcher, Microsoft Research, New York Citymicrosoft.com의 이메일 확인됨
