Hal Daumé III

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Jordan Boyd-GraberFull Professor, University of MarylandVerified email at umiacs.umd.edu
Piyush RaiIIT KanpurVerified email at cse.iitk.ac.in
Amit GoyalAmazon MusicVerified email at amazon.com
Abhishek KumarGoogle BrainVerified email at google.com
John LangfordMicrosoft Research New YorkVerified email at hunch.net
Jagadeesh JagarlamudiGoogleVerified email at umiacs.umd.edu
He HeNew York UniversityVerified email at cs.nyu.edu
Suresh VenkatasubramanianBrown UniversityVerified email at brown.edu
Mohit IyyerAssociate Professor, University of Massachusetts AmherstVerified email at cs.umass.edu
Avishek SahaMachine Learning Scientist, AmazonVerified email at amazon.com
Dan GoldwasserPurdue UniversityVerified email at purdue.edu
Jason EisnerProfessor of Computer Science, Johns Hopkins UniversityVerified email at cs.jhu.edu
Kota YamaguchiCyberAgentVerified email at cyberagent.co.jp
Jesse DodgeAllen Institute for AIVerified email at allenai.org
Margaret MitchellResearch Scientist, Hugging FaceVerified email at huggingface.co
Karl StratosEssential AIVerified email at karlstratos.com
Philip ResnikProfessor, Linguistics and UMIACS, University of MarylandVerified email at umd.edu
Lise GetoorDistinguished Professor of Computer Science & Engineering, University of California, Santa CruzVerified email at ucsc.edu
Alexander C BergProfessor of Computer Science, University of California IrvineVerified email at uci.edu
Tamara L BergAssociate Professor, Computer Science, UNC Chapel HillVerified email at cs.unc.edu

Hal Daumé III

Associate Professor of Computer Science, University of Maryland

Verified email at umiacs.umd.edu - Homepage

Natural language processing machine learning


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Datasheets for datasets T Gebru, J Morgenstern, B Vecchione, JW Vaughan, H Wallach, HD Iii, ... Communications of the ACM 64 (12), 86-92, 2021	2583	2021
Frustratingly easy domain adaptation H Daumé III arXiv preprint arXiv:0907.1815, 2009	2212	2009
Co-regularized multi-view spectral clustering A Kumar, P Rai, H Daume Advances in neural information processing systems 24, 2011	1454	2011
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	1316	2020
Deep unordered composition rivals syntactic methods for text classification M Iyyer, V Manjunatha, J Boyd-Graber, H Daumé III Proceedings of the 53rd annual meeting of the association for computational …, 2015	1149	2015
Domain adaptation for statistical classifiers H Daume III, D Marcu Journal of artificial Intelligence research 26, 101-126, 2006	1102	2006
A co-training approach for multi-view spectral clustering A Kumar, H Daumé Proceedings of the 28th international conference on machine learning (ICML …, 2011	1011	2011
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	950	2019
Generalized multiview analysis: A discriminative latent space A Sharma, A Kumar, H Daume, DW Jacobs 2012 IEEE conference on computer vision and pattern recognition, 2160-2167, 2012	852	2012
Search-based structured prediction H Daumé, J Langford, D Marcu Machine learning 75, 297-325, 2009	719	2009
Learning task grouping and overlap in multi-task learning A Kumar, H Daume III arXiv preprint arXiv:1206.6417, 2012	621	2012
Midge: Generating image descriptions from computer vision detections M Mitchell, J Dodge, A Goyal, K Yamaguchi, K Stratos, X Han, A Mensch, ... Proceedings of the 13th Conference of the European Chapter of the …, 2012	590	2012
Corpus-guided sentence generation of natural images Y Yang, C Teo, H Daumé III, Y Aloimonos Proceedings of the 2011 conference on empirical methods in natural language …, 2011	532	2011
A neural network for factoid question answering over paragraphs M Iyyer, J Boyd-Graber, L Claudino, R Socher, H Daumé III Proceedings of the 2014 conference on empirical methods in natural language …, 2014	468	2014
Incorporating lexical priors into topic models J Jagarlamudi, H Daumé III, R Udupa Proceedings of the 13th Conference of the European Chapter of the …, 2012	452	2012
Opponent modeling in deep reinforcement learning H He, J Boyd-Graber, K Kwok, H Daumé III International conference on machine learning, 1804-1813, 2016	392	2016
When does machine learning {FAIL}? generalized transferability for evasion and poisoning attacks O Suciu, R Marginean, Y Kaya, H Daume III, T Dumitras 27th USENIX Security Symposium (USENIX Security 18), 1299-1316, 2018	354	2018
Bayesian query-focused summarization H Daumé III arXiv preprint arXiv:0907.1814, 2009	322	2009
Learning as search optimization: Approximate large margin methods for structured prediction H Daumé III, D Marcu Proceedings of the 22nd international conference on Machine learning, 169-176, 2005	319	2005
Learning to search in branch and bound algorithms H He, H Daume III, JM Eisner Advances in neural information processing systems 27, 2014	313	2014

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