hypergraph partitioning
6 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in hypergraph partitioning
Latest papers with no code
Bandana: Using Non-volatile Memory for Storing Deep Learning Models
Typical large-scale recommender systems use deep learning models that are stored on a large amount of DRAM.
Evolutionary n-level Hypergraph Partitioning with Adaptive Coarsening
This article presents a novel memetic algorithm which remains effective on larger initial hypergraphs.
Engineering a direct k-way Hypergraph Partitioning Algorithm
We also remove several further bottlenecks in processing large hyperedges, develop a faster contraction algorithm, and a new adaptive stopping rule for local search.
Uniform Hypergraph Partitioning: Provable Tensor Methods and Sampling Techniques
This work is motivated by two issues that arise when a hypergraph partitioning approach is used to tackle computer vision problems: (i) The uniform hypergraphs constructed for higher-order learning contain all edges, but most have negligible weights.
Streaming Min-max Hypergraph Partitioning
In many applications, the data is of rich structure that can be represented by a hypergraph, where the data items are represented by vertices and the associations among items are represented by hyperedges.
Consistency of Spectral Hypergraph Partitioning under Planted Partition Model
Hypergraph partitioning lies at the heart of a number of problems in machine learning and network sciences.
Context-Aware Hypergraph Construction for Robust Spectral Clustering
Using both CAHSM and DHPC, a robust spectral clustering algorithm is developed.
A Hypergraph-Partitioned Vertex Programming Approach for Large-scale Consensus Optimization
In modern data science problems, techniques for extracting value from big data require performing large-scale optimization over heterogenous, irregularly structured data.
