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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
MindX: Denoising Mixed Impulse Poisson-Gaussian Noise Using Proximal Algorithms—0
Parameter Learning for Log-supermodular Distributions—0
How to calculate partition functions using convex programming hierarchies: provable bounds for variational methods—0
Pruning Random Forests for Prediction on a Budget—0
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
Solving Optimization Problems by the Public Goods Game—0
Combinatorial Topic Models using Small-Variance Asymptotics—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
Minimum Weight Perfect Matching via Blossom Belief Propagation—0
Hardness of Online Sleeping Combinatorial Optimization Problems—0
Concept-based Summarization using Integer Linear Programming: From Concept Pruning to Multiple Optimal Solutions—0
The backtracking survey propagation algorithm for solving random K-SAT problems—0
Message Passing and Combinatorial Optimization—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
Learning to Propose Objects—0
Gaze-Enabled Egocentric Video Summarization via Constrained Submodular Maximization—0
Non-projective Dependency-based Pre-Reordering with Recurrent Neural Network for Machine Translation—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
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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