MLT 2024 : 5th International Conference on Machine Learning & Trends

5^th International Conference on Machine Learning & Trends (MLT 2024)

May 25 ~ 26, 2024, Vancouver, Canada

Scope & Topics

5^th International Conference on Machine Learning & Trends (MLT 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & its Trends. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.

Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.

Topics of interest include, but are not limited to, the following

• Applications
  
• Bayesian Network
  
• Computer Vision
  
• Data Mining
  
• Deep Learning
  
• Learning in knowledge-intensive systems
  
• Learning Methods and analysis
  
• Learning Problems
  
• Machine Learning Algorithms
  
• Neural Networks
  
• Predictive Learning
  
• Reinforcement Learning
  
• Supervised Machine Learning
  
• Trends
  
• Unsupervised Machine Learning
  
  

Paper Submission

Authors are invited to submit papers through the conference Submission System by January 13, 2024. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed).

Selected papers from MLT 2024, after further revisions, will be published in the special issues of the following journals.

• Machine Learning and Applications: An International Journal (MLAIJ)
  
• International Journal of Artificial Intelligence & Applications (IJAIA)
  

Important Dates