Google’s Recommender System Breakthrough Detects Semantic Intent

Google quietly published a research paper on personalized semantics for recommender systems like Google Discover and YouTube.
IEEE

Unrolling Nonnegative Matrix Factorization With Group Sparsity for Blind Hyperspectral Unmixing

Abstract: Deep neural networks have shown huge potential in hyperspectral unmixing (HU). However, the large function space increases the difficulty of obtaining the optimal solution with limited ...
IEEE

Matrix Factorization with Landmarks for Spatial Data

Abstract: Matrix factorization (MF) is widely adopted to learn from data, e.g., for data representation and recommendation as well as many database applications such as data imputation and repairing.