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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 901–950 of 1277 papers

TitleStatusHype
Local Branching Relaxation Heuristics for Integer Linear Programs—0
Local Optimal Sets and Bounded Archiving on Multi-objective NK-Landscapes with Correlated Objectives—0
Local Perturb-and-MAP for Structured Prediction—0
New Characterizations and Efficient Local Search for General Integer Linear Programming—0
Logically Synthesized, Hardware-Accelerated, Restricted Boltzmann Machines for Combinatorial Optimization and Integer Factorization—0
Long Term Memory Network for Combinatorial Optimization Problems—0
Low-Rank Extragradient Methods for Scalable Semidefinite Optimization—0
LRM-1B: Towards Large Routing Model—0
Machine Learning and Constraint Programming for Efficient Healthcare Scheduling—0
Machine Learning-assisted High-speed Combinatorial Optimization with Ising Machines for Dynamically Changing Problems—0
Machine Learning for Combinatorial Optimization: a Methodological Tour d'Horizon—0
Machine Learning for the Multi-Dimensional Bin Packing Problem: Literature Review and Empirical Evaluation—0
Machine Learning Methods for Data Association in Multi-Object Tracking—0
MAG-GNN: Reinforcement Learning Boosted Graph Neural Network—0
A Simple and Computationally Trivial Estimator for Grouped Fixed Effects Models—0
Making Sense Of Distributed Representations With Activation Spectroscopy—0
Manipulating Predictions over Discrete Inputs in Machine Teaching—0
Mapping Tractography Across Subjects—0
Material Identification From Radiographs Without Energy Resolution—0
Mathematical Programming Strategies for Solving the Minimum Common String Partition Problem—0
Matroid Bandits: Fast Combinatorial Optimization with Learning—0
Maximizing Non-Monotone DR-Submodular Functions with Cardinality Constraints—0
Maximizing Submodular or Monotone Approximately Submodular Functions by Multi-objective Evolutionary Algorithms—0
Max-Product Belief Propagation for Linear Programming: Applications to Combinatorial Optimization—0
MBL-CPDP: A Multi-objective Bilevel Method for Cross-Project Defect Prediction via Automated Machine Learning—0
MC-CIM: Compute-in-Memory with Monte-Carlo Dropouts for Bayesian Edge Intelligence—0
Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization—0
Memcomputing: Leveraging memory and physics to compute efficiently—0
Message Passing and Combinatorial Optimization—0
Message Passing Variational Autoregressive Network for Solving Intractable Ising Models—0
Metaheuristics and Large Language Models Join Forces: Towards an Integrated Optimization Approach—0
Métodos de Otimização Combinatória Aplicados ao Problema de Compressão MultiFrases—0
MindX: Denoising Mixed Impulse Poisson-Gaussian Noise Using Proximal Algorithms—0
A General Framework for Evaluating Robustness of Combinatorial Optimization Solvers on Graphs—0
MineReduce: an approach based on data mining for problem size reduction—0
Minimizing Energy Consumption in MU-MIMO via Antenna Muting by Neural Networks with Asymmetric Loss—0
Minimizing Polarization and Disagreement in Social Networks via Link Recommendation—0
Minimum Weight Perfect Matching via Blossom Belief Propagation—0
Mixed Uncertainty Sets for Robust Combinatorial Optimization—0
ML4CO: Is GCNN All You Need? Graph Convolutional Neural Networks Produce Strong Baselines For Combinatorial Optimization Problems, If Tuned and Trained Properly, on Appropriate Data—0
Modeling Local Search Metaheuristics Using Markov Decision Processes—0
Eliciting and Distinguishing Between Weak and Incomplete Preferences: Theory, Experiment and Computation—0
MODRL/D-EL: Multiobjective Deep Reinforcement Learning with Evolutionary Learning for Multiobjective Optimization—0
Modular Multi Target Tracking Using LSTM Networks—0
MOEA/D-GM: Using probabilistic graphical models in MOEA/D for solving combinatorial optimization problems—0
MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design—0
Monotone comparative statics for submodular functions, with an application to aggregated deferred acceptance—0
MOOSE-Chem2: Exploring LLM Limits in Fine-Grained Scientific Hypothesis Discovery via Hierarchical Search—0
MRF Optimization with Separable Convex Prior on Partially Ordered Labels—0
mRNA Codon Optimization on Quantum Comptuers—0
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