"Representation Learning in Sequence to Sequence Tasks: Multi-filter Gaussian Mixture Autoencoder"

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Book	Author(s)	Year	Publisher
Tasks in Second Language Learning	Virginia Samuda; Martin Bygate	2008	Palgrave Macmillan UK
Gaussian Processes for Machine Learning	Carl Edward Rasmussen; Christopher K. I. Williams	2005	MIT Press
Gaussian processes for machine learning	Carl Edward Rasmussen	2006	MIT Press
Gaussian Processes for Machine Learning	Carl Edward Rasmussen; Christopher K. I. Williams	2005	MIT Press,
Learning Representation for Multi-View Data Analysis: Models and Applications	Zhengming Ding; Handong Zhao; Yun Fu	1st ed. 2019	Springer International Publishing
Investigating Tasks in Formal Language Learning	María del Pilar García Mayo	2006	Multilingual Matters
Learning to Listen: Tasks for Developing Listening Skills	Alan Maley	January 29, 1982	Cambridge University Press
Performance-Based Learning: Aligning Experiential Tasks and Assessment to Increase Learning	Sally Berman	Corwin	Corwin
Performance-Based Learning: Aligning Experiential Tasks and Assessment to Increase Learning	Sally Berman	June 15, 2007	Corwin Press
Graph Representation Learning	William L. Hamilton		Springer International Publishing
Graph Representation Learning	William L. Hamilton	2020	Morgan & Claypool
Visual Object Tracking from Correlation Filter to Deep Learning	Weiwei Xing; Weibin Liu; Jun Wang; Shunli Zhang; Lihui Wang; Yuxiang Yang; Bowen Song	1st ed. 2021	Springer Nature Singapore
In Order to Learn: How the sequence of topics influences learning	Frank E. Ritter; Josef Nerb; Erno Lehtinen; Timothy O'Shea	2007	Oxford University Press
Multi-Objective Machine Learning	Yaochu Jin	2006	Springer Berlin Heidelberg
Sequence Learning: Paradigms, Algorithms, and Applications	Ron Sun; C.Lee Giles	2001	Springer Berlin Heidelberg
Learning to be prejudiced: growing up in multi-ethnic Britain	Alfred Davey	1983	E. Arnold
Algorithmic Foundation of Multi-Scale Spatial Representation	Zhilin Li	2006	Routledge
Mediated Learning: Teaching, Tasks, and Tools to Unlock Cognitive Potential	Mandia Mentis; Marilyn J. Dunn-Bernstein; Martene Mentis	Corwin	Corwin Press
Inconsequence: Lesbian Representation and the Logic of Sexual Sequence	Annamarie Jagose	2002	Cornell University Press
Inconsequence: lesbian representation and the logic of sexual sequence	Annamarie Jagose	2002	Cornell University Press
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Chapter	Author(s)	Book	Book Authors	Year	Publisher
Representation Learning in Sequence to Sequence Tasks: Multi-filter Gaussian Mixture Autoencoder	Yunhao Yang; Zhaokun Xue	Proceedings of the Future Technologies Conference (FTC) 2021, Volume 1	Kohei Arai	1st ed. 2022	Springer International Publishing
Training Heterogeneous Features in Sequence to Sequence Tasks: Latent Enhanced Multi-filter Seq2Seq Model	Yunhao Yang; Zhaokun Xue	Intelligent Systems and Applications: Proceedings of the 2022 Intelligent Systems Conference (IntelliSys) Volume 2	Kohei Arai	1st ed. 2023	Springer International Publishing
232 Representation learning with autoencoder		Big Data Recommender Systems: Application Paradigms (Computing and Networks)	Osman Khalid (editor), Samee U. Khan (editor), Albert Y. Zomaya (editor)	2019	The Institution of Engineering and Technology
Representation Learning with Smooth Autoencoder	Kongming Liang; Hong Chang; Zhen Cui; Shiguang Shan; Xilin Chen	Computer Vision -- ACCV 2014: 12th Asian Conference on Computer Vision, Singapore, Singapore, November 1-5, 2014, Revised Selected Papers, Part II	Daniel Cremers; Ian Reid; Hideo Saito; Ming-Hsuan Yang	2015	Springer International Publishing
Learning to Navigate in the Gaussian Mixture Surface	Riccardo La Grassa; Ignazio Gallo; Calogero Vetro; Nicola Landro	Computer Analysis of Images and Patterns: 19th International Conference, CAIP 2021, Virtual Event, September 28–30, 2021, Proceedings, Part I	Nicolas Tsapatsoulis; Andreas Panayides; Theo Theocharides; Andreas Lanitis; Constantinos Pattichis; Mario Vento	1st ed. 2021	Springer International Publishing
Gaussian Mixture Filter Based on Variational Bayesian Learning in PPP/SINS	Qing Dai; Lifen Sui; Yuan Tian; Tian Zeng	China Satellite Navigation Conference (CSNC) 2017 Proceedings: Volume II	Jiadong Sun; Jingnan Liu; Yuanxi Yang; Shiwei Fan; Wenxian Yu	1st ed. 2017	Springer Nature Singapore
Gaussian Mixture		Mastering machine learning algorithms: expert techniques for implementing popular machine learning algorithms, fine-tuning your models, and understanding how they work	Giuseppe Bonaccorso	2020	Packt Publishing Ltd
Gaussian mixture		Machine Learning Algorithms	Giuseppe Bonaccorso	2018	Packt Publishing
Multi-Target Tracking with Gaussian Mixture CPHD Filter and Gating Technique	Zhongliang Jing; Han Pan; Yuankai Li; Peng Dong	Non-Cooperative Target Tracking, Fusion and Control: Algorithms and Advances	Zhongliang Jing; Han Pan; Yuankai Li; Peng Dong	1st ed. 2018	Springer International Publishing
Gaussian Filter		Computational Surface and Roundness Metrology	Balasubramanian Muralikrishnan; Jayaraman Raja	2009	Springer London
Gaussian Filter		Encyclopedia of Microfluidics and Nanofluidics	Dongqing Li	2nd ed. 2015	Springer New York
Gaussian Filter		Encyclopedia of Microfluidics and Nanofluidics	Dongqing Li	2008	Springer US
Gaussian Filter		Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library	Adrian Kaehler; Gary Bradski	2016	O'Reilly Media
Gossip-Based Greedy Gaussian Mixture Learning	Nikos Vlassis; Yiannis Sfakianakis; Wojtek Kowalczyk	Advances in Informatics: 10th Panhellenic Conference on Informatics, PCI 2005, Volas, Greece, November 11-13, 2005, Proceedings	Panayiotis Bozanis; Elias N. Houstis	2005	Springer Berlin Heidelberg
Multi-View Representation Learning	G. Muthu Lakshmi; N. Krishnammal	Prediction and Analysis for Knowledge Representation and Machine Learning: Prediction and Analysis for Knowledge Representation and Machine Learning	Avadhesh Kumar; Shrddha Sagar; T. Ganesh Kumar; K. Sampath Kumar	2022	Routledge
Multi-resolution Representation Learning		Computer Vision: A Reference Guide	Katsushi Ikeuchi	2nd ed. 2021	Springer International Publishing
Multi-scale Representation Learning		Computer Vision: A Reference Guide	Katsushi Ikeuchi	2nd ed. 2021	Springer International Publishing
Representation Learning for Underdefined Tasks	Jean-François Bonastre	Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 24th Iberoamerican Congress, CIARP 2019, Havana, Cuba, October 28-31, 2019, Proceedings	Ingela Nyström; Yanio Hernández Heredia; Vladimir Milián Núñez	1st ed. 2019	Springer International Publishing
Sequence-to-Sequence Learning		The Hundred-Page Machine Learning Book	Andriy Burkov	2019	Andriy Burkov
Sequence to Sequence Learning		Dive into Deep Learning	Aston Zhang, Zachary C. Lipton, Mu Li, and Alexander J. Smola	2021	d2l.ai
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