Proposes hypergraph-based dynamic topic modeling using structured low-rank factorizations, temporal regularization, and a nonlinear multinomial likelihood, with local convergence guarantees and error bounds.
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Dynamic Topic Modeling with a Higher-Order Hypergraphical Representation
Proposes hypergraph-based dynamic topic modeling using structured low-rank factorizations, temporal regularization, and a nonlinear multinomial likelihood, with local convergence guarantees and error bounds.