H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 60 Citations 17,375 175 World Ranking 1588 National Ranking 887

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

Hal Daumé spends much of his time researching Artificial intelligence, Natural language processing, Machine learning, Domain adaptation and Simple. When carried out as part of a general Artificial intelligence research project, his work on Image is frequently linked to work in Work, therefore connecting diverse disciplines of study. His study in Natural language processing is interdisciplinary in nature, drawing from both Artificial neural network and Deep learning.

His Machine learning research includes themes of Object, Visualization and Composition. His Domain adaptation study combines topics in areas such as Theoretical computer science, Preprocessor, Adaptation, Range and Perl. His Simple research is multidisciplinary, incorporating elements of Decoding methods, Statistical classification and Mathematical optimization, Heuristic.

His most cited work include:

  • Frustratingly Easy Domain Adaptation (1206 citations)
  • Domain adaptation for statistical classifiers (706 citations)
  • Co-regularized Multi-view Spectral Clustering (629 citations)

What are the main themes of his work throughout his whole career to date?

Artificial intelligence, Machine learning, Natural language processing, Theoretical computer science and Structured prediction are his primary areas of study. Many of his studies on Artificial intelligence involve topics that are commonly interrelated, such as Pattern recognition. Hal Daumé combines subjects such as Multi-task learning, Classifier and Inference with his study of Machine learning.

His research integrates issues of Context, Speech recognition and Word in his study of Natural language processing. Hal Daumé usually deals with Theoretical computer science and limits it to topics linked to Binary tree and Monotonic function. In his study, Annotation is inextricably linked to Oracle, which falls within the broad field of Monotonic function.

He most often published in these fields:

  • Artificial intelligence (68.99%)
  • Machine learning (32.17%)
  • Natural language processing (27.91%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (68.99%)
  • Machine learning (32.17%)
  • Natural language processing (27.91%)

In recent papers he was focusing on the following fields of study:

The scientist’s investigation covers issues in Artificial intelligence, Machine learning, Natural language processing, Process and Machine translation. His Artificial intelligence research incorporates Power and Work. In general Machine learning, his work in Structured prediction is often linked to Ask price linking many areas of study.

His Natural language processing study combines topics from a wide range of disciplines, such as Annotation, SQL and Table. His biological study spans a wide range of topics, including Meta learning, Oracle and Adaptation. He interconnects Algorithm, Face, Active learning and Space in the investigation of issues within Imitation learning.

Between 2019 and 2021, his most popular works were:

  • Language (Technology) is Power: A Critical Survey of "Bias" in NLP (84 citations)
  • Toward Gender-Inclusive Coreference Resolution (24 citations)
  • Language (Technology) is Power: A Critical Survey of "Bias" in NLP (18 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Statistics

Hal Daumé focuses on Artificial intelligence, Machine translation, Natural language processing, Process and Machine learning. The concepts of his Machine translation study are interwoven with issues in Reliability, Debiasing and Unobservable. The Language technology research he does as part of his general Natural language processing study is frequently linked to other disciplines of science, such as Power, Social stratification, Work and Normative reasoning, therefore creating a link between diverse domains of science.

In his papers, Hal Daumé integrates diverse fields, such as Process, Rest and Center. His Machine learning research incorporates themes from Domain, BLEU, Meta learning and Adaptation.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Frustratingly Easy Domain Adaptation

Hal Daume Iii.
meeting of the association for computational linguistics (2007)

1774 Citations

Domain adaptation for statistical classifiers

Hal Daumé;Daniel Marcu.
Journal of Artificial Intelligence Research (2006)

925 Citations

Co-regularized Multi-view Spectral Clustering

Abhishek Kumar;Piyush Rai;Hal Daume.
neural information processing systems (2011)

846 Citations

Deep Unordered Composition Rivals Syntactic Methods for Text Classification

Mohit Iyyer;Varun Manjunatha;Jordan Boyd-Graber;Hal Daumé Iii.
international joint conference on natural language processing (2015)

684 Citations

Generalized Multiview Analysis: A discriminative latent space

Abhishek Sharma;Abhishek Kumar;Hal Daume;David W. Jacobs.
computer vision and pattern recognition (2012)

671 Citations

A Co-training Approach for Multi-view Spectral Clustering

Abhishek Kumar;Hal Daume.
international conference on machine learning (2011)

662 Citations

Search-based structured prediction

Hal Daumé;John Langford;Daniel Marcu.
Machine Learning (2009)

480 Citations

Midge: Generating Image Descriptions From Computer Vision Detections

Margaret Mitchell;Jesse Dodge;Amit Goyal;Kota Yamaguchi.
conference of the european chapter of the association for computational linguistics (2012)

400 Citations

A Neural Network for Factoid Question Answering over Paragraphs

Mohit Iyyer;Jordan Boyd-Graber;Leonardo Claudino;Richard Socher.
empirical methods in natural language processing (2014)

388 Citations

Corpus-Guided Sentence Generation of Natural Images

Yezhou Yang;Ching Teo;Hal Daume Iii;Yiannis Aloimonos.
empirical methods in natural language processing (2011)

381 Citations

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