Cover Image

Semi-supervised learning and domain adaptation in natural language processing /

Bibliographic Details
Main Author:	Søgaard, Anders
Format:	eBook
Language:	English
Published:	San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool, [2013]
Series:	Synthesis digital library of engineering and computer science. Synthesis lectures on human language technologies ; # 21.
Subjects:	Natural language processing (Computer science) Supervised learning (Machine learning) COMPUTERS / Natural Language Processing. learning under bias machine learning natural language processing semi-supervised learning
Online Access:	Connect to the full text of this electronic book

Similar Items

Graph-based semi-supervised learning /
by: Subramanya, Amarnag, et al.
Published: (2014)

Introduction to semi-supervised learning /
by: Zhu, Xiaojin, Ph. D.
Published: (2009)

Introduction to semi-supervised learning /
by: Zhu, Xiaojin, Ph. D.
Published: (2009)

Semi-supervised learning /
Published: (2006)

Learning to rank for information retrieval and natural language processing /
by: Li, Hang, 1965-
Published: (2011)

Semi-supervised learning /
Published: (2006)

Ruo jian du xue xi shi yong zhi nan : yong geng shao de shu ju zuo geng duo de shi qing = Practical weak supervision : doing more with less data /
by: Tok, Wee-Hyong, et al.
Published: (2023)

Machine learning of natural language /
by: Powers, David M. W.
Published: (1989)

Deep learning for natural language processing : a gentle introduction /
by: Surdeanu, Mihai, et al.
Published: (2024)

Linguistic structure prediction /
by: Smith, Noah Ashton
Published: (2011)

Supervised learning : mathematical foundations and real-world applications /
by: Chakrabarty, Dalia
Published: (2025)

Machine learning from weak supervision : an empirical risk minimization approach /
by: Sugiyama, Masashi, 1974-
Published: (2022)

What is supervised machine learning?.
Published: (2019)

Types of supervised machine learning.
Published: (2019)

Kikai gakushū enjinia no tame no Transformers : saisentan no shizen gengo shori raiburari ni yoru moderu kaihatsu /
by: Tunstall, Lewis, et al.
Published: (2022)

The elements of statistical learning : data mining, inference, and prediction : with 200 full-color illustrations /
by: Hastie, Trevor
Published: (2001)

The elements of statistical learning : data mining, inference, and prediction /
by: Hastie, Trevor
Published: (2001)

The elements of statistical learning : data mining, inference, and prediction /
by: Hastie, Trevor
Published: (2009)

The elements of statistical learning : data mining, inference, and prediction /
by: Hastie, Trevor
Published: (2009)

Supervised learning in remote sensing and geospatial science : theory and practice /
by: Maxwell, Aaron E., et al.
Published: (2025)

Digitzing museum objects for teaching & learning : Cabinet.
Published: (2019)

Chinese Computational Linguistics : 18th China National Conference, CCL 2019, Kunming, China, October 18-20, 2019, Proceedings /
Published: (2019)

PyTorch deep learning in 7 days /
Published: (2019)

Shizen gengo shori hen /
by: Saitō, Kōki, 1984-
Published: (2018)

Learn about sentiment analysis with supervised learning in Python with data from the Economic News Article Tone dataset (2016) /
by: Shi, Feng
Published: (2019)

Thinking between the lines : computers and the comprehension of causal descriptions /
by: Borchardt, Gary C.
Published: (1994)

Mian xiang zi ran yu yan chu li de shen du xue xi ke cheng : shen du shen jing wang luo zai ji qi xue xi ren wu de ying yong.
Published: (2017)

Learn about sentiment analysis with supervised learning in R with data from the Economic News Article Tone dataset (2016) /
by: Shi, Feng, active 2019
Published: (2019)

Revealing Media Bias in News Articles : NLP Techniques for Automated Frame Analysis /
by: Hamborg, Felix
Published: (2023)

Natural language processing with TensorFlow : the definitive NLP book to implement the most sought-after machine learning models and tasks /
by: Ganegedara, Thushan
Published: (2022)

Natural Language Processing mit Transformern : Sprachanwendungen mit Hugging Face erstellen /
by: Tunstall, Lewis, et al.
Published: (2023)

Foundation Models for Natural Language Processing : Pre-trained Language Models Integrating Media /
by: Paaß, Gerhard, et al.
Published: (2023)

Requirements Engineering: Foundation for Software Quality : 29th International Working Conference, REFSQ 2023, Barcelona, Spain, April 17-20, 2023, Proceedings /
Published: (2023)

Multi-label dimensionality reduction /
by: Sun, Liang, et al.
Published: (2014)

Boosting : foundations and algorithms /
by: Schapire, Robert E.
Published: (2012)

The mathematics of generalization : the proceedings of the SFI/CNLS Workshop on Formal Approaches to Supervised Learning /
Published: (1995)

Use PyNNDescent and `nessvec` to index high dimensional vectors (word embeddings).
Published: (2022)

Train Word embeddings from scratch with Nessvec and PyTorch.
Published: (2022)

Deep learning for natural language processing /
by: Raaijmakers, Stephan
Published: (2022)

Neural Networks and Deep Learning : A Textbook /
by: Aggarwal, Charu C.
Published: (2023)