
Hypergraph partitions
We suggest a reduction of the combinatorial problem of hypergraph partit...
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Consistency of Spectral Hypergraph Partitioning under Planted Partition Model
Hypergraph partitioning lies at the heart of a number of problems in mac...
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BiPart: A Parallel and Deterministic Multilevel Hypergraph Partitioner
Hypergraph partitioning is used in many problem domains including VLSI d...
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Knowledge Hypergraph Embedding Meets Relational Algebra
Embeddingbased methods for reasoning in knowledge hypergraphs learn a r...
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Neo: Generalizing Confusion Matrix Visualization to Hierarchical and MultiOutput Labels
The confusion matrix, a ubiquitous visualization for helping people eval...
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Bidiagonalization with Parallel Tiled Algorithms
We consider algorithms for going from a "full" matrix to a condensed "ba...
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Embedding Vector Differences Can Be Aligned With Uncertain Intensional Logic Differences
The DeepWalk algorithm is used to assign embedding vectors to nodes in t...
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Distributed Matrix Tiling Using A Hypergraph Labeling Formulation
Partitioning large matrices is an important problem in distributed linear algebra computing (used in ML among others). Briefly, our goal is to perform a sequence of matrix algebra operations in a distributed manner (whenever possible) on these large matrices. However, not all partitioning schemes work well with different matrix algebra operations and their implementations (algorithms). This is a type of data tiling problem. In this work we consider a theoretical model for a version of the matrix tiling problem in the setting of hypergraph labeling. We prove some hardness results and give a theoretical characterization of its complexity on random instances. Additionally we develop a greedy algorithm and experimentally show its efficacy.
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