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There has been an increased interest in discovering heuristics for combinatorial problems on graphs through machine learning.
Probability inequalities for sums of bounded random variables
Wassily Hoeffding · 1963
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Practical Handbook of Curve Fitting
Sandra L Arlinghaus · 1994
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Maximizing the spread of influence through a social network
David Kempe, Jon Kleinberg, and Éva Tardos · 2003
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Neural fitted q iteration–first experiences with a data efficient neural reinforcement learning method
Martin Riedmiller · 2005
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Cost-effective outbreak detection in networks
Jure Leskovec, Andreas Krause, Carlos Guestrin, Christos Faloutsos, Jeanne VanBriesen, and Natalie Glance · 2007
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Cost-effective outbreak detection in networks
Jure Leskovec, Andreas Krause, Carlos Guestrin, Christos Faloutsos, Jeanne VanBriesen, and Natalie Glance · 2007
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Scalable influence maximization for prevalent viral marketing in large-scale social networks
Wei Chen, Chi Wang, and Yajun Wang · 2010
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Limiting the spread of misinformation in social networks
Ceren Budak, Divyakant Agrawal, and Amr El Abbadi · 2011
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Upgrading shortest paths in networks
Bistra Dilkina, Katherine J. Lai, and Carla P. Gomes · 2011
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Recommendations to boost content spread in social networks
Vineet Chaoji, Sayan Ranu, Rajeev Rastogi, and Rushi Bhatt · 2012
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Irie: Scalable and robust influence maximization in social networks
Kyomin Jung, Wooram Heo, and Wei Chen · 2012
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Scalable influence maximization for independent cascade model in large-scale social networks
Chi Wang, Wei Chen, and Yajun Wang · 2012
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Playing atari with deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, and Martin Riedmiller · 2013
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Sketch-based influence maximization and computation: Scaling up with guarantees
Edith Cohen, Daniel Delling, Thomas Pajor, and Renato F Werneck · 2014
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Adam: A method for stochastic optimization, 2014
Diederik P. Kingma and Jimmy Ba · 2014
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Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi, Jan Vondrák, and Andreas Krause · 2014
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Netclus: A scalable framework for locating top-k sites for placement of trajectory-aware services
Shubhadip Mitra, Priya Saraf, Richa Sharma, Arnab Bhattacharya, Sayan Ranuy, and Harsh Bhandari · 2017
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Combinatorial optimization with graph convolutional networks and guided tree search
Zhuwen Li, Qifeng Chen, and Vladlen Koltun · 2018
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Noticeable network delay minimization via node upgrades
Sourav Medya, Jithin Vachery, Sayan Ranu, and Ambuj Singh · 2018
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Reinforcement learning: An introduction
Richard S Sutton and Andrew G Barto · 2018
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Online processing algorithms for influence maximization
Jing Tang, Xueyan Tang, Xiaokui Xiao, and Junsong Yuan · 2018
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Fast and accurate influence maximization on large networks with pruned monte-carlo simulations
Naoto Ohsaka, Takuya Akiba, Yuichi Yoshida, and Ken-ichi Kawarabayashi · 2014
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Trajectory aware macro-cell planning for mobile users
Shubhadip Mitra, Sayan Ranu, Vinay Kolar, Aditya Telang, Arnab Bhattacharya, Ravi Kokku, and Sriram Raghavan · 2015
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Influence maximization in near-linear time: A martingale approach
Youze Tang, Yanchen Shi, and Xiaokui Xiao · 2015
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Akhil Arora, Sainyam Galhotra, and Sayan Ranu · 2017
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Learning combinatorial optimization algorithms over graphs
Hanjun Dai, Elias Khalil, Yuyu Zhang, Bistra Dilkina, and Le Song · 2017
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Inductive representation learning on large graphs
Will Hamilton, Zhitao Ying, and Jure Leskovec · 2017
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Bryan Wilder, Han Ching Ou, Kayla de la Haye, and Milind Tambe · 2018
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Exact combinatorial optimization with graph convolutional neural networks
Maxime Gasse, Didier Chételat, Nicola Ferroni, Laurent Charlin, and Andrea Lodi · 2019
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Cplex 12.9, 2019
IBM · 2019
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Netclus: A scalable framework to mine top-k locations for placement of trajectory-aware services
Shubhadip Mitra, Priya Saraf, Richa Sharma, Arnab Bhattacharya, and Sayan Ranu · 2019
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Learning to solve np-complete problems: A graph neural network for decision tsp
Marcelo Prates, Pedro HC Avelar, Henrique Lemos, Luis C Lamb, and Moshe Y Vardi · 2019
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SNAP Datasets: Stanford large network dataset collection
Jure Leskovec and Andrej Krevl · 2020
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