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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 1151–1200 of 1277 papers

TitleStatusHype
Sample Complexity of Automated Mechanism Design—0
On the performance of different mutation operators of a subpopulation-based genetic algorithm for multi-robot task allocation problems—0
Local Perturb-and-MAP for Structured Prediction—0
Support Vector Algorithms for Optimizing the Partial Area Under the ROC Curve—0
Random-Key Cuckoo Search for the Travelling Salesman Problem—0
Combinatorial Topic Models using Small-Variance Asymptotics—0
Solving Optimization Problems by the Public Goods Game—0
Reinforcement learning based local search for grouping problems: A case study on graph coloring—0
Image Super-Resolution Based on Sparsity Prior via Smoothed l_0 Norm—0
Streaming Algorithms for News and Scientific Literature Recommendation: Submodular Maximization with a d-Knapsack Constraint—0
An Evolutionary Strategy based on Partial Imitation for Solving Optimization Problems—0
Efficient Algorithms for Adversarial Contextual Learning—0
Mapping Tractography Across Subjects—0
On Computationally Tractable Selection of Experiments in Measurement-Constrained Regression Models—0
Towards Integrated Glance To Restructuring in Combinatorial Optimization—0
Level-Based Analysis of Genetic Algorithms for Combinatorial Optimization—0
Smooth and Strong: MAP Inference with Linear Convergence—0
Stochastic Online Greedy Learning with Semi-bandit Feedbacks—0
MOEA/D-GM: Using probabilistic graphical models in MOEA/D for solving combinatorial optimization problems—0
Submodular Functions: from Discrete to Continous Domains—0
Streaming, Distributed Variational Inference for Bayesian Nonparametrics—0
Learning-based Compressive Subsampling—0
Regularization vs. Relaxation: A conic optimization perspective of statistical variable selection—0
Generative Adversarial Networks in Estimation of Distribution Algorithms for Combinatorial OptimizationCode1
Minimum Weight Perfect Matching via Blossom Belief Propagation—0
Deep Boltzmann Machines in Estimation of Distribution Algorithms for Combinatorial OptimizationCode1
Hardness of Online Sleeping Combinatorial Optimization Problems—0
Concept-based Summarization using Integer Linear Programming: From Concept Pruning to Multiple Optimal Solutions—0
Message Passing and Combinatorial Optimization—0
The backtracking survey propagation algorithm for solving random K-SAT problems—0
A Bayesian framework for functional calibration of expensive computational models through non-isometric matching—0
Linear Inverse Problems with Norm and Sparsity Constraints—0
Artificial Catalytic Reactions in 2D for Combinatorial Optimization—0
Pointer NetworksCode1
Non-projective Dependency-based Pre-Reordering with Recurrent Neural Network for Machine Translation—0
Learning to Propose Objects—0
Gaze-Enabled Egocentric Video Summarization via Constrained Submodular Maximization—0
Towards combinatorial clustering: preliminary research survey—0
An Optimal Quadratic Approach to Monolingual Paraphrase Alignment—0
A Dynamic Programming Algorithm for Tree Trimming-based Text Summarization—0
On the Runtime of Randomized Local Search and Simple Evolutionary Algorithms for Dynamic Makespan Scheduling—0
Tight Bounds on Low-degree Spectral Concentration of Submodular and XOS functions—0
Totally Corrective Boosting with Cardinality Penalization—0
Feeder Load Balancing using Neural Network—0
Importance weighting without importance weights: An efficient algorithm for combinatorial semi-bandits—0
Denoising Autoencoders for fast Combinatorial Black Box OptimizationCode1
Inference of hidden structures in complex physical systems by multi-scale clustering—0
Faster quantum mixing for slowly evolving sequences of Markov chains—0
First-order regret bounds for combinatorial semi-bandits—0
Cheaper and Better: Selecting Good Workers for Crowdsourcing—0
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