H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 40 Citations 26,061 111 World Ranking 4625 National Ranking 2297

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Natural language processing

His scientific interests lie mostly in Artificial intelligence, Natural language processing, Sentence, Artificial neural network and Machine translation. His Recurrent neural network and Syntax study, which is part of a larger body of work in Artificial intelligence, is frequently linked to Encoder, bridging the gap between disciplines. His studies in Natural language processing integrate themes in fields like Structure, Word and Vocabulary.

He has included themes like Speech recognition and Pattern recognition in his Artificial neural network study. His research integrates issues of Test data, Urdu and Phrase in his study of Machine translation. The various areas that he examines in his Phrase study include Feature and Sequence.

His most cited work include:

  • Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation (6387 citations)
  • Learning Phrase Representations using RNN Encoder--Decoder for Statistical Machine Translation (3990 citations)
  • Supervised Learning of Universal Sentence Representations from Natural Language Inference Data (958 citations)

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

Holger Schwenk mostly deals with Artificial intelligence, Natural language processing, Machine translation, Speech recognition and Language model. His biological study spans a wide range of topics, including Machine learning and Adaptation. The concepts of his Natural language processing study are interwoven with issues in Arabic and German.

The study incorporates disciplines such as Test data, Translation and Phrase in addition to Machine translation. Holger Schwenk interconnects Word, Space, Transcription and Vocabulary in the investigation of issues within Language model. His research in Artificial neural network intersects with topics in Training set and Pattern recognition.

He most often published in these fields:

  • Artificial intelligence (78.68%)
  • Natural language processing (66.18%)
  • Machine translation (45.59%)

What were the highlights of his more recent work (between 2016-2020)?

  • Artificial intelligence (78.68%)
  • Natural language processing (66.18%)
  • Sentence (19.12%)

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

Holger Schwenk focuses on Artificial intelligence, Natural language processing, Sentence, Machine translation and BLEU. His Artificial intelligence research focuses on Syntax, Transfer of learning, Recurrent neural network, Text processing and Pooling. His Natural language processing research incorporates themes from German and k-nearest neighbors algorithm.

Holger Schwenk has researched Sentence in several fields, including Margin, Document classification, Space and Contrast. He undertakes multidisciplinary investigations into Machine translation and Perspective in his work. His Translation study combines topics in areas such as Training set and Phrase.

Between 2016 and 2020, his most popular works were:

  • Supervised Learning of Universal Sentence Representations from Natural Language Inference Data (958 citations)
  • Very deep convolutional networks for text classification (373 citations)
  • XNLI: Evaluating Cross-lingual Sentence Representations (264 citations)

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

  • Artificial intelligence
  • Machine learning
  • Natural language processing

Artificial intelligence, Sentence, Natural language processing, Machine translation and Encoder are his primary areas of study. Holger Schwenk focuses mostly in the field of Artificial intelligence, narrowing it down to topics relating to Test data and, in certain cases, Swahili and Urdu. His Machine translation research is multidisciplinary, relying on both Space, Syntax, Structure, Semantics and Representation.

His work is dedicated to discovering how Supervised learning, Range are connected with Machine learning and other disciplines. His work deals with themes such as Recurrent neural network, Pooling and Text processing, which intersect with Convolutional neural network. His Classifier research includes themes of Document classification, Vocabulary, Test set and Nearest neighbor search.

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

Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

Kyunghyun Cho;Bart van Merrienboer;Caglar Gulcehre;Dzmitry Bahdanau.
arXiv: Computation and Language (2014)

5746 Citations

Supervised Learning of Universal Sentence Representations from Natural Language Inference Data

Alexis Conneau;Douwe Kiela;Holger Schwenk;Loïc Barrault.
empirical methods in natural language processing (2017)

1028 Citations

Neural Probabilistic Language Models

Yoshua Bengio;Holger Schwenk;Jean-Sébastien Senécal;Fréderic Morin.
Innovations in Machine Learning (2006)

610 Citations

Continuous space language models

Holger Schwenk.
Computer Speech & Language (2007)

604 Citations

On using monolingual corpora in neural machine translation

Çaglar Gülçehre;Orhan Firat;Kelvin Xu;Kyunghyun Cho.
arXiv: Computation and Language (2015)

493 Citations

Very deep convolutional networks for text classification

Alexis Conneau;Holger Schwenk;Loïc Barrault;Yann Lecun.
conference of the european chapter of the association for computational linguistics (2017)

455 Citations

XNLI: Evaluating Cross-lingual Sentence Representations

Alexis Conneau;Ruty Rinott;Guillaume Lample;Adina Williams.
empirical methods in natural language processing (2018)

350 Citations

Boosting Neural Networks

Holger Schwenk;Yoshua Bengio.
Neural Computation (2000)

346 Citations

Very Deep Convolutional Networks for Natural Language Processing.

Alexis Conneau;Holger Schwenk;Loïc Barrault;Yann LeCun.
arXiv: Computation and Language (2016)

298 Citations

Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond

Mikel Artetxe;Holger Schwenk.
Transactions of the Association for Computational Linguistics (2019)

265 Citations

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