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Combinatorial Optimization

Combinatorial Optimization is a category of problems which requires optimizing a function over a combination of discrete objects and the solutions are constrained. Examples include finding shortest paths in a graph, maximizing value in the Knapsack problem and finding boolean settings that satisfy a set of constraints. Many of these problems are NP-Hard, which means that no polynomial time solution can be developed for them. Instead, we can only produce approximations in polynomial time that are guaranteed to be some factor worse than the true optimal solution.

Source: Recent Advances in Neural Program Synthesis

Papers

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Showing 701–750 of 1277 papers

TitleStatusHype
Vulcan: Solving the Steiner Tree Problem with Graph Neural Networks and Deep Reinforcement Learning—0
MC-CIM: Compute-in-Memory with Monte-Carlo Dropouts for Bayesian Edge Intelligence—0
One model Packs Thousands of Items with Recurrent Conditional Query LearningCode1
The Hardness Analysis of Thompson Sampling for Combinatorial Semi-bandits with Greedy Oracle—0
Large Scale Diverse Combinatorial Optimization: ESPN Fantasy Football Player Trades—0
Three-dimensional Cooperative Localization of Commercial-Off-The-Shelf Sensors—0
FastCover: An Unsupervised Learning Framework for Multi-Hop Influence Maximization in Social NetworksCode0
Symbolic Regression via Neural-Guided Genetic Programming Population SeedingCode1
Sample Selection for Fair and Robust Training—0
Interpretable Decision Trees Through MaxSAT—0
Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness—0
OpenABC-D: A Large-Scale Dataset For Machine Learning Guided Integrated Circuit SynthesisCode1
Chaos inspired Particle Swarm Optimization with Levy Flight for Genome Sequence Assembly—0
RL4RS: A Real-World Dataset for Reinforcement Learning based Recommender SystemCode1
A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Meme Stock Prediction—0
Learning-based Memetic Algorithm for Hard-label Textual Attack—0
Robust Correlation Clustering with Asymmetric Noise—0
Efficiently Solve the Max-cut Problem via a Quantum Qubit Rotation AlgorithmCode0
Solving Large Break Minimization Problems in a Mirrored Double Round-robin Tournament Using Quantum AnnealingCode0
Fast Approximations for Job Shop Scheduling: A Lagrangian Dual Deep Learning Method—0
Time Complexity Analysis of Evolutionary Algorithms for 2-Hop (1,2)-Minimum Spanning Tree Problem—0
Hybrid Pointer Networks for Traveling Salesman Problems OptimizationCode1
Assessing Distribution Network Flexibility via Reliability-based P-Q Area Segmentation—0
Learning the Markov Decision Process in the Sparse Gaussian EliminationCode1
Learning to Solve an Order Fulfillment Problem in Milliseconds with Edge-Feature-Embedded Graph Attention—0
Differentiable Scaffolding Tree for Molecule Optimization—0
Learning Scenario Representation for Solving Two-stage Stochastic Integer Programs—0
Deep Dynamic Attention Model with Gate Mechanism for Solving Time-dependent Vehicle Routing Problems—0
What’s Wrong with Deep Learning in Tree Search for Combinatorial Optimization—0
Neural Combinatorial Optimization with Reinforcement Learning : Solving theVehicle Routing Problem with Time Windows—0
Preference Conditioned Neural Multi-objective Combinatorial Optimization—0
Trading Quality for Efficiency of Graph Partitioning: An Inductive Method across Graphs—0
On Learning to Solve Cardinality Constrained Combinatorial Optimization in One-Shot: A Re-parameterization Approach via Gumbel-Sinkhorn-TopK—0
Generative Adversarial Training for Neural Combinatorial Optimization Models—0
Automatic Loss Function Search for Predict-Then-Optimize Problems with Strong Ranking Property—0
WeaveNet: A Differentiable Solver for Non-linear Assignment Problems—0
Neural Extensions: Training Neural Networks with Set Functions—0
An Attention-LSTM Hybrid Model for the Coordinated Routing of Multiple Vehicles—0
Differentiable Scaffolding Tree for Molecular Optimization—0
Learning General Optimal Policies with Graph Neural Networks: Expressive Power, Transparency, and Limits—0
Target Languages (vs. Inductive Biases) for Learning to Act and Plan—0
Rationales for Sequential PredictionsCode1
Simulating the Effects of Eco-Friendly Transportation Selections for Air Pollution Reduction—0
DAN: Decentralized Attention-based Neural Network for the MinMax Multiple Traveling Salesman Problem—0
A new neighborhood structure for job shop scheduling problems—0
Efficient Combinatorial Optimization for Word-level Adversarial Textual Attack—0
RAMA: A Rapid Multicut Algorithm on GPUCode1
High-quality Thermal Gibbs Sampling with Quantum Annealing Hardware—0
Optimization Networks for Integrated Machine Learning—0
Parallel Quasi-concave set optimization: A new frontier that scales without needing submodularity—0
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