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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 251–300 of 1277 papers

TitleStatusHype
Combinatorial Reasoning: Selecting Reasons in Generative AI Pipelines via Combinatorial Optimization—0
Combinatorial Topic Models using Small-Variance Asymptotics—0
Application of Decision Tree Classifier in Detection of Specific Denial of Service Attacks with Genetic Algorithm Based Feature Selection on NSL-KDD—0
Combining Learned Representations for Combinatorial Optimization—0
An interacting replica approach applied to the traveling salesman problem—0
AED: An Anytime Evolutionary DCOP Algorithm—0
Causal Effect Identification in Uncertain Causal Networks—0
Can We Learn Heuristics For Graphical Model Inference Using Reinforcement Learning?—0
An Improved Reinforcement Learning Algorithm for Learning to Branch—0
Systematic and Efficient Construction of Quadratic Unconstrained Binary Optimization Forms for High-order and Dense Interactions—0
Cakewalk Sampling—0
CaDA: Cross-Problem Routing Solver with Constraint-Aware Dual-Attention—0
An Improved ACS Algorithm for the Solutions of Larger TSP Problems—0
An Expandable Machine Learning-Optimization Framework to Sequential Decision-Making—0
Budgeted Influence Maximization for Multiple Products—0
A Dynamic Programming Algorithm for Tree Trimming-based Text Summarization—0
A Class of Linear Programs Solvable by Coordinate-Wise Minimization—0
Reinforcement Learning in Practice: Opportunities and Challenges—0
Bridging Visualization and Optimization: Multimodal Large Language Models on Graph-Structured Combinatorial Optimization—0
Brain-inspired Chaotic Graph Backpropagation for Large-scale Combinatorial Optimization—0
A new neighborhood structure for job shop scheduling problems—0
A Dynamic Algorithm for the Longest Common Subsequence Problem using Ant Colony Optimization Technique—0
Deep Reinforcement Learning for Modelling Protein Complexes—0
Boosting Combinatorial Problem Modeling with Machine Learning—0
Boosting Ant Colony Optimization via Solution Prediction and Machine Learning—0
A new hybrid genetic algorithm for protein structure prediction on the 2D triangular lattice—0
A new dog learns old tricks: RL finds classic optimization algorithms—0
Accelerating Vehicle Routing via AI-Initialized Genetic Algorithms—0
Robust Metric Learning by Smooth Optimization—0
Deep Reinforcement Learning for Online Routing of Unmanned Aerial Vehicles with Wireless Power Transfer—0
Binary sequence set optimization for CDMA applications via mixed-integer quadratic programming—0
Binary matrix factorization on special purpose hardware—0
An Evolutionary Strategy based on Partial Imitation for Solving Optimization Problems—0
A Nested Genetic Algorithm for Explaining Classification Data Sets with Decision Rules—0
A Distribution Evolutionary Algorithm for the Graph Coloring Problem—0
Accelerating Quantum Approximate Optimization Algorithm using Machine Learning—0
BiGrad: Differentiating through Bilevel Optimization Programming—0
Biased Random-Key Genetic Algorithms: A Review—0
An End-to-End Reinforcement Learning Based Approach for Micro-View Order-Dispatching in Ride-Hailing—0
Beyond Statistical Estimation: Differentially Private Individual Computation via Shuffling—0
A Discrete State Transition Algorithm for Generalized Traveling Salesman Problem—0
A Bayesian framework for functional calibration of expensive computational models through non-isometric matching—0
Deep Reinforcement Learning for Traveling Purchaser Problems—0
DeepSimplex: Reinforcement Learning of Pivot Rules Improves the Efficiency of Simplex Algorithm in Solving Linear Programming Problems—0
Differentiable Scaffolding Tree for Molecular Optimization—0
Bayesian preference elicitation for multiobjective combinatorial optimization—0
An Efficient Learning-based Solver Comparable to Metaheuristics for the Capacitated Arc Routing Problem—0
Accelerating Matroid Optimization through Fast Imprecise Oracles—0
Bayesian Optimization for Macro Placement—0
Batch Active Learning via Coordinated Matching—0
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