Picture for David F. Gleich

David F. Gleich

Suboptimality bounds for trace-bounded SDPs enable a faster and scalable low-rank SDP solver SDPLR+

Add code
Jun 14, 2024
Viaarxiv icon

Topological structure of complex predictions

Add code
Aug 06, 2022
Figure 1 for Topological structure of complex predictions
Figure 2 for Topological structure of complex predictions
Figure 3 for Topological structure of complex predictions
Figure 4 for Topological structure of complex predictions
Viaarxiv icon

A flexible PageRank-based graph embedding framework closely related to spectral eigenvector embeddings

Add code
Jul 22, 2022
Figure 1 for A flexible PageRank-based graph embedding framework closely related to spectral eigenvector embeddings
Figure 2 for A flexible PageRank-based graph embedding framework closely related to spectral eigenvector embeddings
Figure 3 for A flexible PageRank-based graph embedding framework closely related to spectral eigenvector embeddings
Figure 4 for A flexible PageRank-based graph embedding framework closely related to spectral eigenvector embeddings
Viaarxiv icon

Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering

Add code
Jun 15, 2020
Figure 1 for Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
Figure 2 for Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
Figure 3 for Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
Figure 4 for Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
Viaarxiv icon

Parameterized Objectives and Algorithms for Clustering Bipartite Graphs and Hypergraphs

Add code
Feb 21, 2020
Figure 1 for Parameterized Objectives and Algorithms for Clustering Bipartite Graphs and Hypergraphs
Figure 2 for Parameterized Objectives and Algorithms for Clustering Bipartite Graphs and Hypergraphs
Figure 3 for Parameterized Objectives and Algorithms for Clustering Bipartite Graphs and Hypergraphs
Figure 4 for Parameterized Objectives and Algorithms for Clustering Bipartite Graphs and Hypergraphs
Viaarxiv icon

Learning Resolution Parameters for Graph Clustering

Add code
Mar 12, 2019
Figure 1 for Learning Resolution Parameters for Graph Clustering
Figure 2 for Learning Resolution Parameters for Graph Clustering
Figure 3 for Learning Resolution Parameters for Graph Clustering
Figure 4 for Learning Resolution Parameters for Graph Clustering
Viaarxiv icon

A Parallel Projection Method for Metric Constrained Optimization

Add code
Jan 29, 2019
Figure 1 for A Parallel Projection Method for Metric Constrained Optimization
Figure 2 for A Parallel Projection Method for Metric Constrained Optimization
Figure 3 for A Parallel Projection Method for Metric Constrained Optimization
Figure 4 for A Parallel Projection Method for Metric Constrained Optimization
Viaarxiv icon

Low rank methods for multiple network alignment

Add code
Sep 21, 2018
Figure 1 for Low rank methods for multiple network alignment
Figure 2 for Low rank methods for multiple network alignment
Figure 3 for Low rank methods for multiple network alignment
Figure 4 for Low rank methods for multiple network alignment
Viaarxiv icon

Correlation Clustering with Low-Rank Matrices

Add code
Mar 17, 2017
Figure 1 for Correlation Clustering with Low-Rank Matrices
Figure 2 for Correlation Clustering with Low-Rank Matrices
Figure 3 for Correlation Clustering with Low-Rank Matrices
Figure 4 for Correlation Clustering with Low-Rank Matrices
Viaarxiv icon

Multi-way Monte Carlo Method for Linear Systems

Add code
Aug 15, 2016
Figure 1 for Multi-way Monte Carlo Method for Linear Systems
Figure 2 for Multi-way Monte Carlo Method for Linear Systems
Viaarxiv icon