DHNE: Network Representation Learning Method for Dynamic Heterogeneous Networks

TransPath: Representation Learning for Heterogeneous Information Networks via Translation Mechanism

In this paper, we propose a novel network representation learning model TransPath to 1 encode heterogeneous information networks (HINs). Traditional network representation learning 2 models aim to learn the embeddings of a homogeneous network. TransPath is able to capture the 3 rich semantic and structure information of a HIN via meta-paths. We take advantage of the concept 4 of translation mec...

Representation of Adsorption Data for the Case of Energetically Heterogeneous Solid Surfaces Using Artificial Neural Network

Dynamic Bayesian Networks : Representation , Inference and Learning

Dynamic Bayesian Networks: Representation, Inference and Learning by Kevin Patrick Murphy Doctor of Philosophy in Computer Science University of California, Berkeley Professor Stuart Russell, Chair Modelling sequential data is important in many areas of science and engineering. Hidden Markov models (HMMs) and Kalman filter models (KFMs) are popular for this because they are simple and flexible....

Modified Dynamic Network Selection Algorithm for Heterogeneous Overlaid Networks

To meet wide expectation and growing demand of mobile users, operators have started to deploy different overlapping radio access network technologies. In heterogonous overlaid networks, network selection decision is delegated to mobile users to avoid processing and signaling overhead. In user centric network selection, users select the network selfishly to maximize their utility and cause undes...

Shared Representation Learning for Heterogeneous Face Recognition

After intensive research, heterogenous face recognition is still a challenging problem. The main difficulties are owing to the complex relationship between heterogenous face image spaces. The heterogeneity is always tightly coupled with other variations, which makes the relationship of heterogenous face images highly nonlinear. Many excellent methods have been proposed to model the nonlinear re...