# Learning-Theoretic Foundations of Algorithm Configuration for Combinatorial Partitioning Problems

@inproceedings{Balcan2016LearningTheoreticFO, title={Learning-Theoretic Foundations of Algorithm Configuration for Combinatorial Partitioning Problems}, author={Maria-Florina Balcan and Vaishnavh Nagarajan and Ellen Vitercik and Colin White}, booktitle={Annual Conference Computational Learning Theory}, year={2016} }

Max-cut, clustering, and many other partitioning problems that are of significant importance to machine learning and other scientific fields are NP-hard, a reality that has motivated researchers to develop a wealth of approximation algorithms and heuristics. [] Key Method Our algorithms learn over common integer quadratic programming and clustering algorithm families: SDP rounding algorithms and agglomerative clustering algorithms with dynamic programming. For our sample complexity analysis, we provide tight…

## 47 Citations

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