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Solving NP-hard/complete combinatorial problems with neural networks is a challenging research area that aims to surpass classical approximate algorithms.
Network flow theory
L. R. Ford Jr · 1956
Earlier work this paper cites.
Shortest connection networks and some generalizations
R. C. Prim · 1957
Earlier work this paper cites.
On a routing problem
B. Richard · 1958
Earlier work this paper cites.
On the evolution of random graphs
P. Erdős, A. Rényi, et al · 1960
Earlier work this paper cites.
Integer programming formulation of traveling salesman problems
C. E. Miller, A. W. Tucker, and R. A. Zemlin · 1960
Earlier work this paper cites.
Optimum locations of switching centers and the absolute centers and medians of a graph
S. L. Hakimi · 1964
Earlier work this paper cites.
Algorithms for minimum coloring, maximum clique, minimum covering by cliques, and maximum independent set of a chordal graph
F. Gavril · 1972
Earlier work this paper cites.
Worst-case analysis of a new heuristic for the travelling salesman problem
N. Christofides · 1976
Earlier work this paper cites.
Branch and bound methods for the traveling salesman problem
E. Balas and P. Toth · 1983
Earlier work this paper cites.
A simple heuristic for the p-centre problem
M. Dyer and A. Frieze · 1985
Earlier work this paper cites.
Clustering to minimize the maximum intercluster distance
T. F. Gonzalez · 1985
Earlier work this paper cites.
A best possible heuristic for the k-center problem
D. S. Hochbaum and D. B. Shmoys · 1985
Earlier work this paper cites.
“neural” computation of decisions in optimization problems
J. J. Hopfield and D. W. Tank · 1985
Earlier work this paper cites.
Local search in routing problems with time windows
M. W. Savelsbergh · 1985
Earlier work this paper cites.
Multiple genome rearrangement and breakpoint phylogeny
D. Sankoff and M. Blanchette · 1998
Earlier work this paper cites.
An effective implementation of the lin–kernighan traveling salesman heuristic
K. Helsgaun · 2000
Earlier work this paper cites.
Combinatorial optimization: networks and matroids
E. L. Lawler · 2001
Earlier work this paper cites.
Concorde tsp solver, 2006
D. Applegate, R. Bixby, V. Chvatal, and W. Cook · 2006
Earlier work this paper cites.
A traveling salesman approach for predicting protein functions
O. Johnson and J. Liu · 2006
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Introduction to Algorithms, 3rd Edition
T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein · 2009
Cited alongside, same era.
Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2015
Cited alongside, same era.
Pointer networks
O. Vinyals, M. Fortunato, and N. Jaitly · 2015
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Pointer graph networks
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Neural execution of graph algorithms
P. Velickovic, R. Ying, M. Padovano, R. Hadsell, and C. Blundell · 2020
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What can neural networks reason about?
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Geometric deep learning: Grids, groups, graphs, geodesics, and gauges
M. M. Bronstein, J. Bruna, T. Cohen, and P. Veličković · 2021
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Neural algorithmic reasoners are implicit planners
A. Deac, P. Velickovic, O. Milinkovic, P. Bacon, J. Tang, and M. Nikolic · 2021
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Persistent message passing
H. Strathmann, M. Barekatain, C. Blundell, and P. Veličković · 2021
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When a worse approximation factor gives better performance: a 3-approximation algorithm for the vertex k-center problem
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Learning combinatorial optimization algorithms over graphs
E. B. Khalil, H. Dai, Y. Zhang, B. Dilkina, and L. Song · 2017
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Semi-supervised classification with graph convolutional networks
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Learning heuristics for the tsp by policy gradient
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Relational inductive bias for physical construction in humans and machines
J. B. Hamrick, K. R. Allen, V. Bapst, T. Zhu, K. R. McKee, J. B. Tenenbaum, and P. W. Battaglia · 2018
Cited alongside, same era.
Graph attention networks
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Neural algorithmic reasoning
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How to transfer algorithmic reasoning knowledge to learn new algorithms?
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A generalist neural algorithmic learner
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Learning the travelling salesperson problem requires rethinking generalization
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A (slightly) improved approximation algorithm for metric tsp, 2022
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Recipe for a general, powerful, scalable graph transformer
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The clrs algorithmic reasoning benchmark
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Parallel algorithms align with neural execution
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Gurobi Optimizer Reference Manual, 2023
Gurobi Optimization, LLC · 2023
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Towards better out-of-distribution generalization of neural algorithmic reasoning tasks
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