Hanna Wallach
Hanna Wallach
Senior Principal Researcher, Microsoft Research
Verified email at dirichlet.net - Homepage
Cited by
Cited by
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
Topic modeling: beyond bag-of-words
HM Wallach
Proceedings of the 23rd international conference on Machine learning, 977-984, 2006
Evaluation methods for topic models
HM Wallach, I Murray, R Salakhutdinov, D Mimno
Proceedings of the 26th annual international conference on machine learning …, 2009
Rethinking LDA: Why priors matter
HM Wallach, DM Mimno, A McCallum
Advances in neural information processing systems, 1973-1981, 2009
Conditional random fields: An introduction
HM Wallach
Technical Reports (CIS), 22, 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
A reductions approach to fair classification
A Agarwal, A Beygelzimer, M Dudík, J Langford, H Wallach
International Conference on Machine Learning, 60-69, 2018
Datasheets for datasets
T Gebru, J Morgenstern, B Vecchione, JW Vaughan, H Wallach, ...
arXiv preprint arXiv:1803.09010, 2018
Efficient training of conditional random fields
H Wallach
Master’s thesis, University of Edinburgh, 2002
Manipulating and measuring model interpretability
F Poursabzi-Sangdeh, DG Goldstein, JM Hofman, JW Vaughan, ...
arXiv preprint arXiv:1802.07810, 2018
Structured topic models for language
HM Wallach
University of Cambridge, 2008
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
Generating summary keywords for emails using topics
M Dredze, HM Wallach, D Puller, F Pereira
Proceedings of the 13th international conference on Intelligent user …, 2008
Database of NIH grants using machine-learned categories and graphical clustering
EM Talley, D Newman, D Mimno, BW Herr II, HM Wallach, GAPC Burns, ...
Nature Methods 8 (6), 443, 2011
Learning the structure of deep sparse graphical models
R Adams, H Wallach, Z Ghahramani
Proceedings of the thirteenth international conference on artificial …, 2010
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
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
Bayesian Poisson tensor factorization for inferring multilateral relations from sparse dyadic event counts
A Schein, J Paisley, DM Blei, H Wallach
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015
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
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, ...
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