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

Structured Convex Optimization Method for Orthogonal Nonnegative Matrix Factorization

Abstract: Orthogonal nonnegative matrix factorization plays an important role for data clustering and machine learning. In this paper, we propose a new optimization model for orthogonal nonnegative ...
Investopedia

Completed Contract Method in Accounting: Key Insights and Examples

Andrew Bloomenthal has 20+ years of editorial experience as a financial journalist and as a financial services marketing writer. Khadija Khartit is a strategy, investment, and funding expert, and an ...
IEEE

Meta Path-Aware Recommendation Method Based on Non-Negative Matrix Factorization in LBSN

Abstract: Location-based social networks (LBSN) is a new type of heterogeneous information network (HIN). The check-in data usually has the characteristics of a large amount of data and high sparsity.
Investopedia

Understanding Straight-Line Basis for Depreciation and Amortization

Daniel Liberto is a journalist with over 10 years of experience working with publications such as the Financial Times, The Independent, and Investors Chronicle. Amy is an ACA and the CEO and founder ...
GitHub

A semi-supervised single channel speech enhancement method using Variational Autoencoder and Non-negative Matrix Factorization

This repository remains the same strustures as A VARIANCE MODELING FRAMEWORK BASED ON VARIATIONAL AUTOENCODERS FOR SPEECH ENHANCEMENT. We replace MCMC-EM algorithm with backpropagation-EM algorithm ...
GitHub

Few-shot Font Generation with Localized Style Representations and Factorization (AAAI 2021)

2 Clova AI Research, NAVER Corp. Automatic few-shot font generation is in high demand because manual designs are expensive and sensitive to the expertise of designers. Existing methods of few-shot ...