Machine learning (ML)-centric resource management in cloud computing: A review and future directions
Cloud computing has rapidly emerged as a model for delivering Internet-based utility
computing services. Infrastructure as a Service (IaaS) is one of the most important and …
computing services. Infrastructure as a Service (IaaS) is one of the most important and …
A survey on machine learning in Internet of Things: Algorithms, strategies, and applications
In the IoT and WSN era, large number of connected objects and sensing devices are
dedicated to collect, transfer, and generate a huge amount of data for a wide variety of fields …
dedicated to collect, transfer, and generate a huge amount of data for a wide variety of fields …
A survey of optimization methods from a machine learning perspective
Machine learning develops rapidly, which has made many theoretical breakthroughs and is
widely applied in various fields. Optimization, as an important part of machine learning, has …
widely applied in various fields. Optimization, as an important part of machine learning, has …
Data Mining The Text Book
C Aggarwal - 2015 - Springer
This textbook explores the different aspects of data mining from the fundamentals to the
complex data types and their applications, capturing the wide diversity of problem domains …
complex data types and their applications, capturing the wide diversity of problem domains …
Normalized cut loss for weakly-supervised cnn segmentation
Most recent semantic segmentation methods train deep convolutional neural networks with
fully annotated masks requiring pixel-accuracy for good quality training. Common weakly …
fully annotated masks requiring pixel-accuracy for good quality training. Common weakly …
Mining heterogeneous information networks: a structural analysis approach
Most objects and data in the real world are of multiple types, interconnected, forming
complex, heterogeneous but often semi-structured information networks. However, most …
complex, heterogeneous but often semi-structured information networks. However, most …
[كتاب][B] Mining heterogeneous information networks: principles and methodologies
Real world physical and abstract data objects are interconnected, forming gigantic,
interconnected networks. By structuring these data objects and interactions between these …
interconnected networks. By structuring these data objects and interactions between these …
[كتاب][B] Data mining: concepts and techniques
Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and
methods for mining patterns, knowledge, and models from various kinds of data for diverse …
methods for mining patterns, knowledge, and models from various kinds of data for diverse …
[PDF][PDF] A new simplex sparse learning model to measure data similarity for clustering
The Laplacian matrix of a graph can be used in many areas of mathematical research and
has a physical interpretation in various theories. However, there are a few open issues in the …
has a physical interpretation in various theories. However, there are a few open issues in the …
Symmetric nonnegative matrix factorization for graph clustering
Nonnegative matrix factorization (NMF) provides a lower rank approximation of a
nonnegative matrix, and has been successfully used as a clustering method. In this paper …
nonnegative matrix, and has been successfully used as a clustering method. In this paper …