Special Sessions

SS12-Advances on Machine Learning, Deep Learning and Data Analytics


DOWNLOAD: Special Session


Session Chair/ Session Organizers:
1. Dr. Achyut Shankar, Assistant Professor, Department of Computer Science & Engineering, Amity School of Engineering & Technology, Amity University, Noida, Uttar Pradesh, India
2. Dr. Pavika Sharma, Assistant Professor, Department of Electronics & Communication Engineering, Amity School of Engineering & Technology, Amity University, Noida, Uttar Pradesh, India

SESSION DESCRIPTION

In recent years, Machine learning has drastically revolutionized almost every field of application such as logistics, diagnostics, robotics, healthcare, manufacturing, retail, transportation, agriculture, business, industrial control, fault detection, quality control, surface inspection, web applications, environmental monitoring, biomedical systems, decision support systems, security, system identification, communications, and electronic services. Further, advancements in machine learning has lead us to the area of deep learning which is capable of generating hierarchical high-level representations from massive volumes of raw data automatically. Deep-learning-based systems with an ability to enhance the human performance are being deployed in the real world mostly in technology companies, financial institutions, and the e-commerce industry.
This special session aims to attract professionals, researchers, and practitioners to represent theoretical as well as application-based advancements in the field of machine learning, deep learning, and handling of big data through machine learning and deep learning. Challenges and solutions which provide better and successful analytics resulting in secure information and system designing, developing, testing, understanding, accessing, processing, sharing, discovering, storing, evaluating, valuing, preserving, visualizing, and exploration will be appreciated.


RECOMMENDED TOPICS
Topics to be discussed in this special session include (but are not limited to) the following scope:
• Machine Learning & Deep Learning in Health
• Machine Learning & Deep Learning in Energy Applications
• Machine Learning & Deep Learning for NLP
• Machine Learning & Deep Learning in Cyber Security Applications and Implementations
• Machine Learning & Deep Learning in Information and Cyber Security
• Machine Learning & Deep Learning in Privacy Issues
• Machine Learning & Deep Learning in Cryptography and Cryptanalysis
• Machine Learning & Deep Learning in Security Risk Analysis, Modeling, Evaluation and Management
• Machine Learning & Deep Learning in Critical Information and Infrastructure Security
• Machine Learning & Deep Learning in Security Standards, Protocols and Policies
• Machine Learning & Deep Learning in RFID, NFC, 6G and Beyond 6G Security
• Machine Learning & Deep Learning in Operating System Security
• Machine Learning & Deep Learning in Clouds and Virtual Machine Security
• Machine Learning & Deep Learning in Biometric based Security
• Machine Learning & Deep Learning in Mobile Communication and Application Security
• Machine Learning & Deep Learning in Securing Social Networks
• Machine Learning & Deep Learning in Securing Networks, Computers, Services, Systems, Databases and Devices
• Machine Learning & Deep Learning in Web and Web Application Security
• Machine Learning & Deep Learning in Intrusion and Anomaly Detection and Prevention Systems
• Machine Learning & Deep Learning in Recent Theory, Trends, Technologies and Applications
• Big data Analytics
• Data Mining
• Data Stream Mining
• Data mining algorithms for Big data
• Deep Learning and its applications



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