"Diffusion-Based Graph Contrastive Learning for Recommendation with Implicit Feedback"

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Book	Author(s)	Year	Publisher
Graph-Based Semi-Supervised Learning	Amarnag Subramanya; Partha Pratim Talukdar		Springer International Publishing
Graph-Based Semi-Supervised Learning	Amarnag Subramanya, Partha Pratim Talukdar	2014	Morgan & Claypool Publishers
Feedback for Learning	Susan Askew	2000	Routledge
How Implicit Is Implicit Learning?	Dianne C. Berry	1997	Oxford University Press
Reinforcement Learning for Optimal Feedback Control: A Lyapunov-Based Approach	Rushikesh Kamalapurkar; Patrick Walters; Joel Rosenfeld; Warren Dixon	1st ed. 2018	Springer International Publishing
Handbook of implicit learning	Michael A. Stadler	1998	Sage Publications
Visible Learning: Feedback	John Hattie; Shirley Clarke	2018	Routledge
Graph Representation Learning	William L. Hamilton		Springer International Publishing
Graph Representation Learning	William L. Hamilton	2020	Morgan & Claypool
Learning in Economic Systems with Expectations Feedback	Jan Wenzelburger	2006	Springer Berlin Heidelberg
Implicit Learning: 50 Years On	Axel Cleeremans; Viktor Allakhverdov; Maria Kuvaldina	2019	Routledge
Deep Learning for Matching in Search and Recommendation	Jun Xu	2020	NOW PUBLISHERS
Truncated Predictor Based Feedback Designs for Linear Systems with Input Delay	Yusheng Wei; Zongli Lin	1st ed. 2021	Springer International Publishing
Graph-based keyword spotting	Andreas Fischer; Michael Stauffer; Kaspar Riesen	2020	World Scientific Publishing
Graph-Based Proof Procedures for Horn Clauses	RAATZ	1990	Birkhäuser Boston
Standards-Based Learning for Students with Disabilities	Marsha Craft- Tripp; Allan Glatthorn	2000	Routledge
Graph-Powered Machine Learning	Alessandro Nego	2021	‎ Manning Publications
Coding for Channels with Feedback	James M. Ooi (auth.)	1998	Springer US
Coding for Channels with Feedback	James M. Ooi	1998	Springer US
Realtime Data Mining: Self-Learning Techniques for Recommendation Engines	Alexander Paprotny; Michael Thess	2013	Springer International Publishing
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Chapter	Author(s)	Book	Book Authors	Year	Publisher
Diffusion-Based Graph Contrastive Learning for Recommendation with Implicit Feedback	Lingzi Zhang; Yong Liu; Xin Zhou; Chunyan Miao; Guoxin Wang; Haihong Tang	Database Systems for Advanced Applications: 27th International Conference, DASFAA 2022, Virtual Event, April 11–14, 2022, Proceedings, Part II	Arnab Bhattacharya; Janice Lee Mong Li; Divyakant Agrawal; P. Krishna Reddy; Mukesh Mohania; Anirban Mondal; Vikram Goyal; Rage Uday Kiran	1st ed. 2022	Springer International Publishing
Implicit Feedback Mining for Recommendation	Yan Song; Ping Yang; Chunhong Zhang; Yang Ji	Big Data Computing and Communications: First International Conference, BigCom 2015, Taiyuan, China, August 1-3, 2015, Proceedings	Yu Wang; Hui Xiong; Shlomo Argamon; XiangYang Li; JianZhong Li	1st ed. 2015	Springer International Publishing
Contrastive Graph Learning with Graph Convolutional Networks	G. Nagendar; Ramachandrula Sitaram	Document Analysis Systems: 15th IAPR International Workshop, DAS 2022, La Rochelle, France, May 22–25, 2022, Proceedings	Seiichi Uchida; Elisa Barney; Véronique Eglin	1st ed. 2022	Springer International Publishing
Item Recommendation from Implicit Feedback	Steffen Rendle	Recommender Systems Handbook	Francesco Ricci; Lior Rokach; Bracha Shapira	3rd ed. 2022	Springer US
DCAR: Deep Collaborative Autoencoder for Recommendation with Implicit Feedback	Jiong Wang; Neng Gao; Jia Peng; Jingjie Mo	Artificial Neural Networks and Machine Learning – ICANN 2019: Text and Time Series: 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part IV	Igor V. Tetko; Věra Kůrková; Pavel Karpov; Fabian Theis	1st ed. 2019	Springer International Publishing
Cross-perspective Graph Contrastive Learning	Shiyang Lin; Chenhe Dong; Ying Shen	Knowledge Science, Engineering and Management: 15th International Conference, KSEM 2022, Singapore, August 6–8, 2022, Proceedings, Part I	Gerard Memmi; Baijian Yang; Linghe Kong; Tianwei Zhang; Meikang Qiu	1st ed. 2022	Springer International Publishing
Reinforcing Recommendation Using Implicit Negative Feedback	Danielle H. Lee; Peter Brusilovsky	User Modeling, Adaptation, and Personalization: 17th International Conference, UMAP 2009, formerly UM and AH, Trento, Italy, June 22-26, 2009, Proceedings	Geert-Jan Houben; Gord McCalla; Fabio Pianesi; Massimo Zancanaro	2009	Springer Berlin Heidelberg
Online Personalized Recommendation Based on Streaming Implicit User Feedback	Zhisheng Wang; Qi Li; Ye Liu; Wei Liu; Jian Yin	Web Technologies and Applications: 17th Asia-Pacific Web Conference, APWeb 2015, Guangzhou, China, September 18-20, 2015, Proceedings	Reynold Cheng; Bin Cui; Zhenjie Zhang; Ruichu Cai; Jia Xu	1st ed. 2015	Springer International Publishing
722 Graph-based approaches for recommendation		Personalization Techniques And Recommender Systems (Series in Machine Perception and Artificial Intelligence ???) (Series in Machine Perception and Artificial. . . Perception and Artifical Intelligence)	Gulden Uchyigit, Gulden Uchyigit, Matthew Y Ma	2008	World Scientific Publishing Company
Graph-based Models for Explainable Recommendation		Explainable Recommendation: A Survey and New Perspectives	YONGFENG ZHANG; XU CHEN.	2020	NOW Publishers
Fast ALS-Based Tensor Factorization for Context-Aware Recommendation from Implicit Feedback	Balázs Hidasi; Domonkos Tikk	Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings, Part II	Peter A. Flach; Tijl De Bie; Nello Cristianini	2012	Springer Berlin Heidelberg
Label Contrastive Coding Based Graph Neural Network for Graph Classification	Yuxiang Ren; Jiyang Bai; Jiawei Zhang	Database Systems for Advanced Applications: 26th International Conference, DASFAA 2021, Taipei, Taiwan, April 11–14, 2021, Proceedings, Part I	Christian S. Jensen; Ee-Peng Lim; De-Nian Yang; Wang-Chien Lee; Vincent S. Tseng; Vana Kalogeraki; Jen-Wei Huang; Chih-Ya Shen	1st ed. 2021	Springer International Publishing
Knowledge Graph-based Explainable Recommendation		Explainable Recommendation: A Survey and New Perspectives	YONGFENG ZHANG; XU CHEN.	2020	NOW Publishers
Content-Based Recommendation for Stacked-Graph Navigation	Alejandro Toledo; Kingkarn Sookhanaphibarn; Ruck Thawonmas; Frank Rinaldo	Multimedia Services in Intelligent Environments: Advances in Recommender Systems	George A. Tsihrintzis; Maria Virvou; Lakhmi C. Jain	2013	Springer International Publishing
Recommending Based on Implicit Feedback	Dietmar Jannach; Lukas Lerche; Markus Zanker	Social Information Access: Systems and Technologies	Peter Brusilovsky; Daqing He	1st ed. 2018	Springer International Publishing
Learning Robust Representation Through Graph Adversarial Contrastive Learning	Jiayan Guo; Shangyang Li; Yue Zhao; Yan Zhang	Database Systems for Advanced Applications: 27th International Conference, DASFAA 2022, Virtual Event, April 11–14, 2022, Proceedings, Part I	Arnab Bhattacharya; Janice Lee Mong Li; Divyakant Agrawal; P. Krishna Reddy; Mukesh Mohania; Anirban Mondal; Vikram Goyal; Rage Uday Kiran	1st ed. 2022	Springer International Publishing
Implicit Feedback		Practical Machine Learning with Spark: Uncover Apache Spark’s Scalable Performance with High-Quality Algorithms Across NLP, Computer Vision and ML(English Edition)	Gourav Gupta, Dr. Manish Gupta, Dr. Inder Singh Gupta	2022	BPB Publications
Implicit feedback		Probabilistic Machine Learning: An Introduction (Adaptive Computation and Machine Learning series)	Kevin P. Murphy	2022	The MIT Press
Heterogeneous Dyadic Multi-task Learning with Implicit Feedback	Simon Moura; Amir Asarbaev; Massih-Reza Amini; Yury Maximov	Neural Information Processing: 25th International Conference, ICONIP 2018, Siem Reap, Cambodia, December 13–16, 2018, Proceedings, Part III	Long Cheng; Andrew Chi Sing Leung; Seiichi Ozawa	1st ed. 2018	Springer International Publishing
Feedback-Guided Attributed Graph Embedding for Relevant Video Recommendation	Taofeng Xue; Xinzhou Dong; Wei Zhuo; Beihong Jin; He Chen; Wenhai Pan et al.	Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track: European Conference, ECML PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings, Part IV	Yuxiao Dong; Dunja Mladenić; Craig Saunders	1st ed. 2021	Springer International Publishing
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