graph theory

WNCG Student Wins Award for Paper on Epidemic Processes

Ph.D. student Jessica Hoffmann received second place in the INFORMS Nicholson Student Paper competition. She received the award for her recent paper "Learning Graphs from Noisy Epidemic Cascades" with her advisor, WNCG professor Constantine Caramanis.

Epidemics are a powerful framework for modeling human and computer viruses, as well as influence, rumors, information and disinformation. Hoffmann’s research develops algorithms to solve an inverse problem on graphs, in order to understand the precise spreading mechanisms.

Quadratic Maximization Problems

Several optimization problems in machine learning, data mining and graph theory can be expressed as quadratic maximization problems, subject to integrality, positivity, or sparsity constraints. These include Sparse PCA, Densest Subgraph, Nonnegative matrix factorization, MaxCut, Maximum clique and many others. These problems are known to be computationally intractable and, in many cases, hard to approximate. WNCG Profs.

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