Luke Veldt - Texas A&M University (TAMU) Scholar

academic article
- Chodrow, P. S., Veldt, N., & Benson, A. R (2021). Generative hypergraph clustering: From blockmodels to modularity. Science Advances. 7(28),
- Veldt, N., Gleich, D. F., Wirth, A., & Saunderson, J (2019). Metric-Constrained Optimization for Graph Clustering Algorithms. SIAM Journal on Mathematics of Data Science. 1(2), 333-355.
conference paper
- Liu, M., Veldt, N., Song, H., Li, P., & Gleich, D. F. (2021). Strongly Local Hypergraph Diffusions for Clustering and Semi-supervised Learning. 2092-2103.
- Veldt, N., Benson, A. R., & Kleinberg, J. (2021). The Generalized Mean Densest Subgraph Problem. 1604-1614.
- Amburg, I., Veldt, N., & Benson, A. (2020). Clustering in graphs and hypergraphs with categorical edge labels. 706-717.
- Veldt, N., Benson, A. R., & Kleinberg, J. (2020). Minimizing Localized Ratio Cut Objectives in Hypergraphs. 1708-1718.
- Veldt, N., Wirth, A., & Gleich, D. F. (2020). Parameterized Correlation Clustering in Hypergraphs and Bipartite Graphs. 1868-1876.
- Veldt, N., Gleich, D., & Wirth, A. (2019). Learning Resolution Parameters for Graph Clustering. 1909-1919.
- Veldt, N., Gleich, D. F., & Wirth, A. (2018). A Correlation Clustering Framework for Community Detection. 439-448.
- Nassar, H., Veldt, N., Mohammadi, S., Grama, A., & Gleich, D. F. (2018). Low Rank Spectral Network Alignment. 619-628.
- Veldt, N., Wirth, A. I., & Gleich, D. F. (2017). Correlation Clustering with Low-Rank Matrices. 1025-1034.

Veldt, Luke Assistant Professor