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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 1001–1050 of 1277 papers

TitleStatusHype
A topological analysis of the space of recipes—0
Attention-based Reinforcement Learning for Combinatorial Optimization: Application to Job Shop Scheduling Problem—0
Attention Round for Post-Training Quantization—0
A Tutorial about Random Neural Networks in Supervised Learning—0
A Tutorial on Dual Decomposition and Lagrangian Relaxation for Inference in Natural Language Processing—0
A Two-stage Framework and Reinforcement Learning-based Optimization Algorithms for Complex Scheduling Problems—0
A Unified Framework for Combinatorial Optimization Based on Graph Neural Networks—0
A Unified Pre-training and Adaptation Framework for Combinatorial Optimization on Graphs—0
A Unifying Survey of Reinforced, Sensitive and Stigmergic Agent-Based Approaches for E-GTSP—0
Automated Graph Genetic Algorithm based Puzzle Validation for Faster Game Design—0
Automatic Loss Function Search for Predict-Then-Optimize Problems with Strong Ranking Property—0
Automatic Rank Selection for High-Speed Convolutional Neural Network—0
Auxiliary-task Based Deep Reinforcement Learning for Participant Selection Problem in Mobile Crowdsourcing—0
A Weighted Common Subgraph Matching Algorithm—0
A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Meme Stock Prediction—0
Balancing Pareto Front exploration of Non-dominated Tournament Genetic Algorithm (B-NTGA) in solving multi-objective NP-hard problems with constraints—0
Barriers for the performance of graph neural networks (GNN) in discrete random structures. A comment on~schuetz2022combinatorial,angelini2023modern,schuetz2023reply—0
Batch Active Learning via Coordinated Matching—0
Bayesian Optimization for Macro Placement—0
Bayesian preference elicitation for multiobjective combinatorial optimization—0
Beyond Statistical Estimation: Differentially Private Individual Computation via Shuffling—0
Biased Random-Key Genetic Algorithms: A Review—0
BiGrad: Differentiating through Bilevel Optimization Programming—0
Binary matrix factorization on special purpose hardware—0
Binary sequence set optimization for CDMA applications via mixed-integer quadratic programming—0
Boosting Ant Colony Optimization via Solution Prediction and Machine Learning—0
Boosting Combinatorial Problem Modeling with Machine Learning—0
Bottleneck potentials in Markov Random Fields—0
Brain-inspired Chaotic Graph Backpropagation for Large-scale Combinatorial Optimization—0
Bridging Visualization and Optimization: Multimodal Large Language Models on Graph-Structured Combinatorial Optimization—0
Budgeted Influence Maximization for Multiple Products—0
CaDA: Cross-Problem Routing Solver with Constraint-Aware Dual-Attention—0
Cakewalk Sampling—0
Can We Learn Heuristics For Graphical Model Inference Using Reinforcement Learning?—0
Causal Effect Identification in Uncertain Causal Networks—0
Causal Discovery with Reinforcement Learning—0
CCJA: Context-Coherent Jailbreak Attack for Aligned Large Language Models—0
Chaos inspired Particle Swarm Optimization with Levy Flight for Genome Sequence Assembly—0
Characterization of Locality in Spin States and Forced Moves for Optimizations—0
Assessing Distribution Network Flexibility via Reliability-based P-Q Area Segmentation—0
Charged particle tracking with quantum annealing-inspired optimization—0
CHARME: A chain-based reinforcement learning approach for the minor embedding problem—0
Chases and Escapes, and Optimization Problems—0
Cheaper and Better: Selecting Good Workers for Crowdsourcing—0
Chemical Reaction Optimization for the Set Covering Problem—0
Cluster Ensembles --- A Knowledge Reuse Framework for Combining Multiple Partitions—0
Clustering Binary Data by Application of Combinatorial Optimization Heuristics—0
Clustering Method for Time-Series Images Using Quantum-Inspired Computing Technology—0
The Curious Case of Class Accuracy Imbalance in LLMs: Post-hoc Debiasing via Nonlinear Integer Programming—0
CoCo: Learning Strategies for Online Mixed-Integer Control—0
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