Call for Papers
Call for Papers | 征稿主题

2022 International Conference on Big Data Analysis and Machine Learning (BDAML 2022) is the premier forum for the presentation of new advances and research results in the fields of Big Data and Machine Learning. The conference will bring together leading researchers, engineers and scientists in the domain of interest from around the world. Topics of interest for submission include, but are not limited to:

CFP Brochure


Data and Big Data Science

数据及大数据科学

Machine Learning Theory and Applications

机器学习理论与应用

Artificial Intelligence Technology and Application 人工智能技术与应用

Information Retrieval
信息检索

Multi-modal Machine learning
多模态机器学习

NLP sentimental analysis
NLP情感分析

Big Data Analytics

大数据分析

Weakly supervised learning

弱监督学习

Graph neural networks and applications

图神经网络及应用

Data Science Models and Approaches

数据科学模型和方法

Reinforcement learning and applications

强化学习和应用

AI Algorithms

人工智能算法

Algorithms for Big Data丨大数据算法

Data Mining and Machine Learning Tools

数据挖掘和机器学习工具

Artificial Intelligence tools & Applications, Bioinformatics

人工智能工具与应用、生物信息学

Big Data Search and Information Retrieval Techniques

大数据搜索与信息检索技术

Fuzzy Logic

模糊逻辑

Natural Language Processing

自然语言处理

Data Mining and Knowledge Discovery Approaches

数据挖掘和知识发现方法

Performance optimization of machine learning algorithms

机器学习算法的性能优化

Computer Vision and Speech Understanding

计算机视觉和语音理解

Machine Learning Techniques for Big Data

大数据机器学习技术

Programming models and tools for machine learning

机器学习的编程模型和工具

Intelligent image and video analysis

智能图像和视频分析

Big Data Acquisition, Integration, Cleaning, and Best Practices

大数据采集、集成、清理和最佳实践

Machine learning model compression algorithms

机器学习模型压缩算法

Heuristic and AI Planning Strategies and Tools, Computational Theories of Learning

启发式和人工智能规划策略和工具,学习的计算理论 

Big Data and Deep Learning

大数据和深度学习

Hardware-aware machine learning model synthesis

硬件感知机器学习模型合成

Hybrid Intelligent Systems

混合智能系统

In-Memory Systems and Platforms for Big Data Analytics

用于大数据分析的内存系统和平台

Power-efficient algorithms for machine learning

机器学习的节能算法

Intelligent System Architectures

智能系统架构

Big Data and High Performance Computing

大数据和高性能计算

Specialized hardware architecture for machine learning

用于机器学习的专用硬件架构

Visual Analytics Algorithms and Foundations

可视化分析算法和基础

Cyber-Infrastructure for Big Data

大数据网络基础设施

Machine learning based compiler techniques

基于机器学习的编译器技术

Graph and Context Models for Visualization

用于可视化的图形和上下文模型

Performance Evaluation Reports for Big Data Systems

大数据系统性能评估报告

Machine learning based power efficient algorithms

基于机器学习的节能算法

Visual Representation and Interaction

视觉表示和交互

Resource Management Approaches for Big Data Systems

大数据系统的资源管理方法

Deep and Reinforcement Learning

深度强化学习

Speech Recognition

语音识别

Big Data Applications for Internet of Things

物联网大数据应用

Machine Learning for Network Slicing Optimization

用于网络切片优化的机器学习

face recognition

人脸识别

Mobile Applications of Big Data

大数据的移动应用

Machine Learning for 5G system

5G 系统的机器学习

Palmprint Recognition

掌纹识别

Big Data Applications for Smart City

智慧城市的大数据应用

Machine Learning for User Behavior Prediction

用于用户行为预测的机器学习

Expert System

专家系统

Data Streaming Applications

数据流应用

New Innovative Machine Learning Methods

新的创新机器学习方法

Smart search

智能搜索

Scalability of Big Data Systems

大数据系统的可扩展性

Performance Analysis of Machine Learning Algorithms

机器学习算法的性能分析

Intelligent Voice Recording System

智能语音录入系统

Big Data Privacy and Security

大数据隐私和安全

Experimental evaluations of machine learning

机器学习的实验评估

Recommended system

推荐系统

Big Data Archival and Preservatio

大数据归档与保存

Machine learning for multimedia

多媒体机器学习

 

Analytics Reasoning and Sense-making on Big Data

大数据分析推理和意义构建

Machine learning for Internet of Things

物联网机器学习

 

Big Data Transformation, and Presentation

大数据转换和呈现

Machine learning for security and protection

用于安全和保护的机器学习

 

Data mining in heterogeneous networks

异构网络中的数据挖掘

Distributed and decentralized machine learning algorithms

分布式和去中心化机器学习算法

 

 

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2022 International Conference on Big Data Analysis and Machine Learning(BDAML 2022)