We introduce the idea of contrastive learning (CL) into the nonnegative matrix factorization (NMF) for community detection (CD)for the first time, solving the problems of the existing work. The two modules are mutually reinforcing and naturally coupled: On the one hand, with the help of CL,...
Deep Autoencoder-like NMF with Contrastive Regularization and Feature Relationship Preservation 2023, Expert Systems with Applications Show abstract Log-based sparse nonnegative matrix factorization for data representation 2022, Knowledge-Based Systems Show abstract Decoding clinical biomarker space of COVID-19...
To address such a limited learning capability, deep learning researchers have developed ONMF models using neural Model formulation This section discusses the design of the proposed DAutoED-ONMF model in detail. We start by introducing key notations and some preliminaries used in the model ...
contrastiveanalysishypothesis(CAH)wasfirstputbyfamouslinguistRobertLadoin1947.LinguistsadvocatesthebeliefthatthebasicproblemsinL2learningdonotresultfromanyessentialdifficultiesinthenewlanguagefeaturesbutprimarilyfromlearners’L1habits(Odlin,2001,p15).CharlesFriesstates,“Themosteffectivematerials(forforeignlanguageteaching)...