2020 2nd International Conference on Machine Learning, Big Data and Business Intelligence
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2020 2nd International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI 2020) provide a premier forum for the presentation of new advances and research results in the fields of machine learning, big data and business intelligence. The conference will bring together leading researchers, social workers and scientists in the domain of interest from around the world. Please click on the call for papers for the specific conference for further details. 


Topics of interest for submission include, but are not limited to:

1.Machine Learning1.机器学习

Deep and Reinforcement learning

Pattern recognition and classification for networks

Machine learning for network slicing optimization

Machine learning for 5G system

Machine learning for user behavior prediction

New innovative machine learning methods

Optimization of machine learning methods

Performance analysis of machine learning algorithms

Experimental evaluations of machine learning

Data mining in heterogeneous networks

Machine learning for multimedia

Machine learning for Internet of Things

Machine learning for security and protection

Distributed and decentralized machine learning algorithms

深入和强化学习

网络的模式识别和分类

用于网络切片优化的机器学习

机器学习5G系统

用于用户行为预测的机器学习

新的创新机器学习方法

优化机器学习方法

机器学习算法的性能分析

机器学习的实验评估

异构网络中的数据挖掘

机器学习多媒体

物联网机器学习

机器学习的安全和保护

分布式和分散式机器学习算法

2.Big Data2.大数据

Big Data Analytics

Data Science Models and Approaches

Algorithms for Big Data

Big Data Search and Information Retrieval Techniques

Big Data Acquisition, Integration, Cleaning, and Best Practices

Big Data and Deep Learning

Scalable Computing Models, Theories, and Algorithms

In-Memory Systems and Platforms for Big Data Analytics

Big Data and High Performance Computing

Cyber-Infrastructure for Big Data

Performance Evaluation Reports for Big Data Systems

Storage Systems (including file systems, NoSQL, and RDBMS)

Resource Management Approaches for Big Data Systems

Many-Core Computing and Accelerators

Big Data Applications for Internet of Things

Mobile Applications of Big Data

Big Data Applications for Smart City

Data Streaming Applications

Fault Tolerance and Reliability

Scalability of Big Data Systems

Big Data Privacy and Security

Big Data Archival and Preservation

Visual Analytics Algorithms and Foundations

Graph and Context Models for Visualization

Big Data Transformation, and Presentation

大数据分析

数据科学模型和方法

大数据的算法

大数据搜索和信息检索技术

大数据采集,集成,清洁和最佳实践

大数据和深度学习

可扩展的计算模型,理论和算法

用于大数据分析的内存系统和平台

大数据和高性能计算

大数据的网络基础设施

大数据系统的绩效评估报告

存储系统(包括文件系统,NoSQL和RDBMS)

大数据系统的资源管理方法

多核计算和加速器

物联网大数据应用

大数据的移动应用

智能城市的大数据应用

数据流应用程序

容错性和可靠性

大数据系统的可扩展性

大数据隐私和安全

大数据存档和保存

可视化分析算法和基础

可视化的图形和上下文模型

大数据转换和演示

3.Business Intelligence3.商务智能

Intelligent Computing Methodologies and Applications

Evolutionary Computing and Learning 

Swarm Intelligence and Optimization 

Signal Processing and Pattern Recognition 

Image Processing and Information Security 

Virtual Reality and Human-Computer Interaction 

Business Intelligence and Multimedia Technology 

Healthcare Informatics Theory and Methods 

Natural Language Processing and Computingal Linguistics 

Intelligent Computing in Robotics 

Intelligent Control and Automation 

Intelligent Data Fusion 

Intelligent Agent and Web Applications 

Intelligent Fault Diagnosis 

Intelligent cloud-support communications

Intelligent ressource allocation

Intelligent energy-aware/green communications

Intelligent software defined networks

Intelligent positioning and navigation systems

Intelligent wireless communications

Intelligent wireless sensor networks

智能计算方法和应用

进化计算和学习

群体智能与优化

信号处理和模式识别

图像处理与信息安全

虚拟现实与人机交互

商业智能和多媒体技术

医疗保健信息学理论与方法

自然语言处理与计算语言学

机器人智能计算

智能控制与自动化

智能数据融合

智能代理和Web应用程序

智能故障诊断

智能云支持通信

智能资源分配

智能能源感知/绿色通信

智能软件定义网络

智能定位和导航系统

智能无线通信

智能无线传感器网络

4. Other related topics4.其他相关主题