6 papers
Maximum-distance nonnegative matrix factorization for unmixing highly mixed grain-size distribution data
Qianqian Qi, Zhongming Chen, Peter G. M. van der Heijden
Unmixing grain-size distribution data into several end-members can help reveal sediment provenance, transport, and sedimentation processes. Traditional end-member unmixing methods…
Identification of NMF by choosing maximum-volume basis vectors
Qianqian Qi, Zhongming Chen, Peter G. M. van der Heijden
In nonnegative matrix factorization (NMF), minimum-volume-constrained NMF is a widely used framework for identifying the solution of NMF by making basis vectors as similar as possi…
Unmixing highly mixed grain size distribution data via maximum volume constrained end member analysis
Qianqian Qi, Zhongming Chen, Peter G. M. van der Heijden
End member analysis (EMA) unmixes grain size distribution (GSD) data into a mixture of end members (EMs), thus helping understand sediment provenance and depositional regimes and p…
Nonnegative matrix factorizations and related compositional models: Equivalence, identifiability, and an application on the grain-size analysis of sediments
Qianqian Qi, Peter G. M. van der Heijden, Maarten A. Prins
Across fields such as machine learning, social science, and geology, considerable attention has been given to models that factorize a nonnegative matrix into the product of two or…
Correspondence Analysis and PMI-Based Word Embeddings: A Comparative Study
Qianqian Qi, Ayoub Bagheri, David J. Hessen +1
Popular word embedding methods such as GloVe and Word2Vec are related to the factorization of the pointwise mutual information (PMI) matrix. In this paper, we establish a formal co…
Correspondence analysis: handling cell-wise outliers via the reconstitution algorithm
Qianqian Qi, David J. Hessen, Aike N. Vonk +1
Correspondence analysis (CA) is a popular technique to visualize the relationship between two categorical variables. CA uses the data from a two-way contingency table and is affect…