"Data Selection via Semi-supervised Recursive Autoencoders for SMT Domain Adaptation"

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Book	Author(s)	Year	Publisher
Semi-Supervised Learning and Domain Adaptation in Natural Language Processing	Anders Søgaard		Springer International Publishing
Semi-Supervised Learning and Domain Adaptation in Natural Language Processing	Anders Sogaard	2013	Morgan & Claypool Publishers
Kernel Based Algorithms for Mining Huge Data Sets: Supervised, Semi-supervised, and Unsupervised Learning	Te-Ming Huang; Vojislav Kecman; Ivica Kopriva	2006	Springer Berlin Heidelberg
Semi-Supervised Learning	Olivier Chapelle; Bernhard Schölkopf; Alexander Zien	2006	MIT Press
Semi-Supervised Learning	Olivier Chapelle; Bernhard Scholkopf; Alexander Zien	2006	The MIT Press
Semi-supervised learning	Olivier Chapelle; Bernhard Schölkopf; Alexander Zien	2010	MIT Press
Semi-Supervised Dependency Parsing	Wenliang Chen; Min Zhang	1st ed. 2015	Springer Nature Singapore
Domain Adaptation for Visual Understanding	Richa Singh; Mayank Vatsa; Vishal M. Patel; Nalini Ratha	1st ed. 2020	Springer International Publishing
Introduction to Semi-Supervised Learning	Xiaojin Zhu; Andrew. B Goldberg		Springer International Publishing
Graph-Based Semi-Supervised Learning	Amarnag Subramanya; Partha Pratim Talukdar		Springer International Publishing
Introduction to semi-supervised learning	Zhu X., Goldberg A.B	2009	Morgan
Graph-Based Semi-Supervised Learning	Amarnag Subramanya, Partha Pratim Talukdar	2014	Morgan & Claypool Publishers
Supervised and Unsupervised Learning for Data Science	Michael W. Berry; Azlinah Mohamed; Bee Wah Yap	1st ed. 2020	Springer International Publishing
Recursive Block Coding for Image Data Compression	Paul Michael Farrelle	1990	Springer New York
Advances in Domain Adaptation Theory	Ievgen Redko; Emilie Morvant; Amaury Habrard; Marc Sebban and Younès Bennani	2019	Elsevier
Semi-Supervised and Unsupervised Machine Learning: Novel Strategies	Amparo Albalate	2011	John Wiley & Sons
Domain Adaptation in Computer Vision Applications	Gabriela Csurka	1st ed. 2017	Springer International Publishing
Systems Engineering for Commercial Aircraft: A Domain-Specific Adaptation	Scott Jackson	2015	Routledge
Domain Driven Data Mining	Longbing Cao; Philip S. Yu; Chengqi Zhang; Yanchang Zhao	2010	Springer US
Data flow analysis techniques for test data selection	Sandra Rapps	1981	Courant Institute of Mathematical Sciences, New York University
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Chapter	Author(s)	Book	Book Authors	Year	Publisher
Data Selection via Semi-supervised Recursive Autoencoders for SMT Domain Adaptation	Yi Lu; Derek F. Wong; Lidia S. Chao; Longyue Wang	Machine Translation: 10th China Workshop, CWMT 2014, Macau, China, November 4-6, 2014. Proceedings	Xiaodong Shi; Yidong Chen	2014	Springer Berlin Heidelberg
Knowledge Distillation for Semi-supervised Domain Adaptation	Mauricio Orbes-Arteainst; Jorge Cardoso; Lauge Sørensen; Christian Igel; Sebastien Ourselin; Marc Modat et al.	OR 2. 0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging: Second International Workshop, OR 2. 0 2019, and Second International Workshop, MLCN 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings	Luping Zhou; Duygu Sarikaya; Seyed Mostafa Kia; Stefanie Speidel; Anand Malpani; Daniel Hashimoto; Mohamad Habes; Tommy Löfstedt; Kerstin Ritter; Hongzhi Wang	1st ed. 2019	Springer International Publishing
iCPE: A Hybrid Data Selection Model for SMT Domain Adaptation	Longyue Wang; Derek F. Wong; Lidia S. Chao; Yi Lu; Junwen Xing	Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data: 12th China National Conference, CCL 2013 and First International Symposium, NLP-NABD 2013, Suzhou, China, October 10-12, 2013, Proceedings	Maosong Sun; Min Zhang; Dekang Lin; Haifeng Wang	2013	Springer Berlin Heidelberg
Self-supervised Bernoulli Autoencoders for Semi-supervised Hashing	Ricardo Ñanculef; Francisco Mena; Antonio Macaluso; Stefano Lodi; Claudio Sartori	Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 25th Iberoamerican Congress, CIARP 2021, Porto, Portugal, May 10–13, 2021, Revised Selected Papers	João Manuel R. S. Tavares; João Paulo Papa; Manuel González Hidalgo	1st ed. 2021	Springer International Publishing
Supervised domain adaptation		Natural Language Processing	Jacob Eisenstein	2018	MIT Press, and are posted here under the Creative Commons license CC-BY-NC-ND
Active Supervised Domain Adaptation	Avishek Saha; Piyush Rai; Hal Daumé III; Suresh Venkatasubramanian; Scott L. DuVall	Machine Learning and Knowledge Discovery in Databases, Part III: European Conference, ECML PKDD 2010, Athens, Greece, September 5-9, 2011, Proceedings, Part III	Dimitrios Gunopulos; Thomas Hofmann; Donato Malerba; Michalis Vazirgiannis	2011	Springer Berlin Heidelberg
Predicting Adverse Drug-Drug Interactions via Semi-supervised Variational Autoencoders	Meihao Hou; Fan Yang; Lizhen Cui; Wei Guo	Web and Big Data: 4th International Joint Conference, APWeb-WAIM 2020, Tianjin, China, September 18-20, 2020, Proceedings, Part II	Xin Wang; Rui Zhang; Young-Koo Lee; Le Sun; Yang-Sae Moon	1st ed. 2020	Springer International Publishing
Active and Semi-supervised Data Domain Description	Nico Görnitz; Marius Kloft; Ulf Brefeld	Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2009, Bled, Slovenia, September 7-11, 2009, Proceedings, Part I	Wray Buntine; Marko Grobelnik; Dunja Mladenic; John Shawe-Taylor	2009	Springer Berlin Heidelberg
A Novel Metric Learning Framework for Semi-supervised Domain Adaptation	Rakesh Kumar Sanodiya; Chinmay Sharma; Sai Satwik; Aravind Challa; Sathwik Rao; Leehter Yao	Neural Information Processing: 28th International Conference, ICONIP 2021, Sanur, Bali, Indonesia, December 8–12, 2021, Proceedings, Part I	Teddy Mantoro; Minho Lee; Media Anugerah Ayu; Kok Wai Wong; Achmad Nizar Hidayanto	1st ed. 2021	Springer International Publishing
Domain Adaptation for SMT Using Sentence Weight	Xinpeng Zhou; Hailong Cao; Tiejun Zhao	Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data: 14th China National Conference, CCL 2015 and Third International Symposium, NLP-NABD 2015, Guangzhou, China, November 13-14, 2015, Proceedings	Maosong Sun; Zhiyuan Liu; Min Zhang; Yang Liu	1st ed. 2015	Springer International Publishing
Supervised Domain Adaptation for Sentiment Regression	Jian Xu; Hao Yin; Shoushan Li; Guodong Zhou	Social Media Processing: 6th National Conference, SMP 2017, Beijing, China, September 14-17, 2017, Proceedings	Xueqi Cheng; Weiying Ma; Huan Liu; Huawei Shen; Shizheng Feng; Xing Xie	1st ed. 2017	Springer Nature Singapore
Supervised Domain Adaptation via Label Alignment for Opinion Expression Extraction	Yifan Zhang; Arjun Mukherjee; Fan Yang	Computational Linguistics and Intelligent Text Processing: 18th International Conference, CICLing 2017, Budapest, Hungary, April 17–23, 2017, Revised Selected Papers, Part II	Alexander Gelbukh	1st ed. 2018	Springer International Publishing
EEG-Based Emotion Recognition via Joint Domain Adaptation and Semi-supervised RVFL Network	Wenjuan Wang; Yong Peng; Wanzeng Kong	Advances in Intelligent Automation and Soft Computing	Xiaolong Li	1st ed. 2022	Springer International Publishing
Semi-Supervised Extreme Instance Selection vs Semi-Supervised Learning		Exploiting the power of group differences: using patterns to solve data analysis problems	Dong, Guozhu	2019	Morgan & Claypool Publishers
Semi-Supervised Extreme Instance Selection vs Semi-Supervised Learning		Exploiting the Power of Group Differences: Using Patterns to Solve Data Analysis Problems	Lise Getoor (editor), Jiawei Han (editor), Guozhu Dong	2019	Morgan & Claypool Publishers
Semi-supervised learning via constraints	Wei Pan and Xiaotong Shen	Prediction and discovery: AMS-IMS-SIAM Joint Summer Research Conference, Machine and Statistical Learning: Prediction and Discovery, June 25-29, 2006, Snowbird, Utah /	Verducci, Joseph S.; Shen, Xiaotong,; Lafferty, John.	2007.	American Mathematical Society,
The \(\ell _{2, 1}\) -Norm Stacked Robust Autoencoders via Adaptation Regularization for Domain Adaptation	Shuai Yang; Yuhong Zhang; Yi Zhu; Han Ding; Xuegang Hu	Artificial Intelligence and Security: 5th International Conference, ICAIS 2019, New York, NY, USA, July 26-28, 2019, Proceedings, Part II	Xingming Sun; Zhaoqing Pan; Elisa Bertino	1st ed. 2019	Springer International Publishing
Semi-supervised Subspace Co-Projection for Multi-class Heterogeneous Domain Adaptation	Min Xiao; Yuhong Guo	Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part II	Annalisa Appice; Pedro Pereira Rodrigues; Vítor Santos Costa; João Gama; Alípio Jorge; Carlos Soares	1st ed. 2015	Springer International Publishing
Semi-supervised Domain Adaptation for Weakly Labeled Semantic Video Object Segmentation	Huiling Wang; Tapani Raiko; Lasse Lensu; Tinghuai Wang; Juha Karhunen	Computer Vision – ACCV 2016: 13th Asian Conference on Computer Vision, Taipei, Taiwan, November 20-24, 2016, Revised Selected Papers, Part I	Shang-Hong Lai; Vincent Lepetit; Ko Nishino; Yoichi Sato	1st ed. 2017	Springer International Publishing
Online Meta-learning for Multi-source and Semi-supervised Domain Adaptation	Da Li; Timothy Hospedales	Computer Vision – ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XVI	Andrea Vedaldi; Horst Bischof; Thomas Brox; Jan-Michael Frahm	1st ed. 2020	Springer International Publishing
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