ICDSIP 2023 conference is an open forum for the exchange of state-of-the-art knowledge concerning Intelligent Computing and Machine Learning. The conference solicits papers on all aspects of Intelligent Computing and Machine Learning, including data collection, data preparation, model building, training, and application deployment. All the full papers will go through a rigorous blind peer-reviewing process.
Topics
ICDSIP 2023 conference solicits submissions describing original and previously unpublished research. Specific topics of interest include but are not limited to:
● AI and Evolutionary Algorithms
● Algorithms and Programming
● Algorithms and Systems for Big Data Search
● Analytics Reasoning and Sense-making on Big Data
● Artificial Intelligence
● Big Data Analytics and Metrics
● Big Data Architectures
● Big Data Economics
● Big Data Encryption
● Big Data for Business Model
● Big Data for Enterprise, Government and Society
● Big Data Management
● Big Data Models and Algorithms
● Big Data Open Platforms
● Big Data Persistence and Preservation
● Big Data Protection, Integrity and Privacy
● Big Data Quality and Provenance Control
● Big Data Search and Mining
● Big Data Transformation and Presentation
● Data Mining in Heterogeneous Networks
● Decision Support Systems
● Deep and Reinforcement Learning
● Distributed and Decentralized Machine Learning Algorithms
● Experimental Evaluations of Machine Learning
● Foundational Models for Big Data
● Intelligent Data Mining and Farming
● Intelligent Information Systems
● Intelligent Networks
● Intelligent Tutoring Systems
● Learning and Adaptive Sensor Fusion
● Machine Learning for 5G System
● Machine Learning for Internet of Things
● Machine Learning for Multimedia
● Machine Learning for Network Slicing Optimization
● Machine Learning for Security and Protection
● Machine Learning for User Behavior Prediction
● Models and Languages for Big
● New Innovative Machine Learning Methods
● Optimization of Machine Learning Methods
● Pattern Recognition and Classification for Networks
● Performance Analysis of Machine Learning Algorithms
● Privacy-Preserving Big Data Analytics
● Reasoning Strategies
● Software Tools for AI
● Techniques for Big Data Processing
● Visual Representation and Interaction