Fetching the paper…
Reading the bibliography…
Social networks are frequently polluted by rumors, which can be detected by advanced models such as graph neural networks.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J Williams. 1992 · 1992
Earlier work this paper cites.
An Upper Bound on the Bayesian Error Bars for Generalized Linear Regression
Cazhaow S. Qazaz, Christopher K. I. Williams, and Christopher M. Bishop. 1997 · 1997
Earlier work this paper cites.
Reinforcement learning for continuous action using stochastic gradient ascent
Hajime Kimura and Shigenobu Kobayashi. 1998 · 1998
Earlier work this paper cites.
Actor-critic algorithms. In Advances in neural information processing systems . 1008–1014
Vijay R Konda and John N Tsitsiklis. 2000 · 2000
Earlier work this paper cites.
Policy gradient methods for reinforcement learning with function approximation. In Advances in neural information processing systems . 1057–1063
Richard S Sutton, David A McAllester, Satinder P Singh, and Yishay Mansour. 2000 · 2000
Earlier work this paper cites.
Simulation-based optimization of Markov reward processes
Peter Marbach and John N Tsitsiklis. 2001 · 2001
Earlier work this paper cites.
The Optimal Reward Baseline for Gradient-Based Reinforcement Learning. In UAI
Lex Weaver and Nigel Tao. 2001 · 2001
Earlier work this paper cites.
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning. In J. Mach. Learn. Res
Evan Greensmith, Peter L. Bartlett, and Jonathan Baxter. 2004 · 2004
Earlier work this paper cites.
Is Long Horizon Reinforcement Learning More Difficult Than Short Horizon Reinforcement Learning?
Ruosong Wang, Simon S. Du, Lin F. Yang, and Sham M. Kakade. 2020 · 2005
Earlier work this paper cites.
Pattern recognition and machine learning . Vol. 4
Christopher M Bishop and Nasser M Nasrabadi. 2006 · 2006
Earlier work this paper cites.
A Contextual-Bandit Approach to Personalized News Article Recommendation. WWW ’10, 661–670
Lihong Li, Wei Chu, John Langford, and Robert E. Schapire. 2010 · 2010
Earlier work this paper cites.
Everyone’s an Influencer: Quantifying Influence on Twitter. In WSDM ’11 . 65–74
Eytan Bakshy, Jake M. Hofman, Winter A. Mason, and Duncan J. Watts. 2011 · 2011
Earlier work this paper cites.
How Visibility and Divided Attention Constrain Social Contagion
Nathan Hodas and Kristina Lerman. 2012 · 2012
Earlier work this paper cites.
Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski, Stig Petersen, Charles Beattie, Amir Sadik, Ioannis Antonoglou, Helen King, Dharshan Kumaran, Daan Wierstra, Shane Legg, and Demis Hassabis. 2015 · 2015
Earlier work this paper cites.
"Why Should I Trust You?": Explaining the Predictions of Any Classifier (KDD) . ACM, 1135–1144
Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin. 2016 · 2016
Cited alongside, same era.
Learning Reporting Dynamics during Breaking News for Rumour Detection in Social Media
Arkaitz Zubiaga, Maria Liakata, and Rob Procter. 2016 · 2016
Cited alongside, same era.
Semi-Supervised Classification with Graph Convolutional Networks. In ICLR 2017
Thomas N. Kipf and Max Welling. 2017 · 2017
Cited alongside, same era.
Detect Rumors in Microblog Posts Using Propagation Structure via Kernel Learning. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017, Vancouver, Canada, July 30 - August 4, Volume 1: Long Papers , Regina Barzilay and Min-Yen Kan (Eds.). 708–717
Jing Ma, Wei Gao, and Kam-Fai Wong. 2017 · 2017
Cited alongside, same era.
Adversarial Attack on Graph Structured Data, Vol. 80. PMLR 2018, 1115–1124
Rewards Prediction-Based Credit Assignment for Reinforcement Learning With Sparse Binary Rewards
Minah Seo, Luiz Felipe Vecchietti, Sangkeum Lee, and Dongsoo Har. 2019 · 2019
Later among the works it cites.
Adversarial Examples for Graph Data: Deep Insights into Attack and Defense. In IJCAI-19 . 4816–4823
Huijun Wu, Chen Wang, Yuriy Tyshetskiy, Andrew Docherty, Kai Lu, and Liming Zhu. 2019 · 2019
Later among the works it cites.
How Powerful are Graph Neural Networks?. In International Conference on Learning Representations
Keyulu Xu, Weihua Hu, Jure Leskovec, and Stefanie Jegelka. 2019 · 2019
Later among the works it cites.
Adversarial Attacks on Graph Neural Networks via Meta Learning. In ICLR 2019
Daniel Zügner and Stephan Günnemann. 2019 · 2019
Later among the works it cites.
Reinforcement Learning Interpretation Methods: A Survey
Alnour Alharin, Thanh-Nam Doan, and Mina Sartipi. 2020 · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Hanjun Dai, Hui Li, Tian Tian, Xin Huang, Lin Wang, Jun Zhu, and Le Song. 2018 · 2018
Cited alongside, same era.
Counterfactual Multi-Agent Policy Gradients. In Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence,(AAAI-18) , Sheila A. McIlraith and Kilian Q. Weinberger (Eds.). AAAI Press, 2974–2982
Jakob N. Foerster, Gregory Farquhar, Triantafyllos Afouras, Nantas Nardelli, and Shimon Whiteson. 2018 · 2018
Cited alongside, same era.
Modeling Relational Data with Graph Convolutional Networks. In The Semantic Web , Aldo Gangemi, Roberto Navigli, Maria-Esther Vidal, Pascal Hitzler, Raphaël Troncy, Laura Hollink, Anna Tordai, and Mehwish Alam (Eds.). 593–607
Michael Schlichtkrull, Thomas N. Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, and Max Welling. 2018 · 2018
Cited alongside, same era.
Reinforcement learning: An introduction
Richard S Sutton and Andrew G Barto. 2018 · 2018
Cited alongside, same era.
The Mirage of Action-Dependent Baselines in Reinforcement Learning
G. Tucker, Surya Bhupatiraju, Shixiang Shane Gu, Richard E. Turner, Zoubin Ghahramani, and Sergey Levine. 2018 · 2018
Cited alongside, same era.
Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines
Cathy Wu, Aravind Rajeswaran, Yan Duan, Vikash Kumar, Alexandre M. Bayen, Sham M. Kakade, Igor Mordatch, and P. Abbeel. 2018 · 2018
Cited alongside, same era.
Adversarial Attacks on Neural Networks for Graph Data. In KDD ’18 . 2847–2856
Daniel Zügner, Amir Akbarnejad, and Stephan Günnemann. 2018 · 2018
Cited alongside, same era.
Adversarial Attacks on Node Embeddings via Graph Poisoning. In PMLR 2019 , Vol. 97. 695–704
Aleksandar Bojchevski and Stephan Günnemann. 2019 · 2019
Cited alongside, same era.
Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks
Tian Bian, Xi Xiao, Tingyang Xu, Peilin Zhao, Wenbing Huang, Yu Rong, and Junzhou Huang. 2020 · 2020
Later among the works it cites.
Generalization and Representational Limits of Graph Neural Networks
Vikas K Garg, Stefanie Jegelka, and Tommi S Jaakkola. 2020 · 2020
Later among the works it cites.
GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social Media. In ACL 2020 . 505–514
Yi-Ju Lu and Cheng-Te Li. 2020 · 2020
Later among the works it cites.
Towards More Practical Adversarial Attacks on Graph Neural Networks. In Advances in Neural Information Processing Systems , H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, and H. Lin (Eds.), Vol. 33. 4756–4766
Jiaqi Ma, Shuangrui Ding, and Qiaozhu Mei. 2020 · 2020
Later among the works it cites.
Graph Neural Networks Exponentially Lose Expressive Power for Node Classification. In 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020 . OpenReview.net
Kenta Oono and Taiji Suzuki. 2020 · 2020
Later among the works it cites.
Rumor Detection on Social Media with Graph Structured Adversarial Learning. In IJCAI-20 . 1417–1423
Xiaoyu Yang, Yuefei Lyu, Tian Tian, Yifei Liu, Yudong Liu, and Xi Zhang. 2020 · 2020
Later among the works it cites.
Graph Neural Networks: Architectures, Stability, and Transferability
Luana Ruiz, Fernando Gama, and Alejandro Ribeiro. 2021 · 2021
Later among the works it cites.
CED: Credible Early Detection of Social Media Rumors
Changhe Song, Cheng Yang, Huimin Chen, Cunchao Tu, Zhiyuan Liu, and Maosong Sun. 2021 · 2021
Later among the works it cites.