State representation learning (SRL) is a particular case of feature learning in which the features to learn are low dimensional, evolve through time, and are influenced by actions or interactions. From: Neural Networks, 2018 About this pageSet alert Also in subject area: Computer ScienceDiscover ...
Participation Constraints Total Participation− Each entity is involved in the relationship. Total participation is represented by double lines. Partial participation− Not all entities are involved in the relationship. Partial participation is represented by single lines. ...
The binary states of entries in foreground support F are modeled by a Markov Random Field because the foreground objects are contiguous pieces with relatively small size. Based on the first order MRFs, the following regularizer on F is used: (154)‖Cvec(F)‖l1=∑(ij,kl)∈N|Fij−Fkl|...
Attributes are the properties of entities. Attributes are represented by means of ellipses. Every ellipse represents one attribute and is directly connected to its entity (rectangle).If the attributes are composite, they are further divided in a tree like structure. Every node is then connected to...
The new framework based on deep learning was built to learn the original and global representation of a miRNA-disease pair. First, diverse biological premises about miRNAs and diseases were combined to construct the embedding layer in the left part of the framework, from a biological perspective....
Structure of the Improved PCANet For the traditional PCANet, binary hashing is used in the output layer, where the output values are set to be 1 and 0 for positive entries and other entries, respectively. However, the negative entries also carry the structural information of the image. ...
In addition, the relationships between vertices in a tree are not bi-directional, which limits the representation of the interactions between geographical objects. The cause of these problems is related to the tree structure limiting the representation of geographic knowledge [16]. Second, the logic...
big data and cognitive computing Article Leveraging Image Representation of Network Traffic Data and Transfer Learning in Botnet Detection Shayan Taheri, Milad Salem and Jiann-Shiun Yuan * Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL 32816, USA; shayan....
This has been proposed to overcome the drawback of multi-scale data structures, which support only a limited number of scale intervals with data redundancy [15,25]. A few vario-scale models have been successfully carried out, including the Binary Line Generalization tree (BLG tree) [36], ...