CMLA 2025 : 7th International Conference on Machine Learning & Applications

July 19-20, 2025Toronto, Canada

7th International Conference on Machine Learning & Applications (CMLA 2025)

July 19 ~ 20, 2025, Toronto, Canada

Hybrid -- Registered authors can present their work online or face to face.

Scope & Topics

7th International Conference on Machine Learning & Applications (CMLA 2025) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.

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

  • 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
  • Unsupervised Machine Learning

Paper Submission

Authors are invited to submit papers through the conference Submission System by June 28, 2025(Final Call). 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 The proceedings of the conference will be published by Computer Science Conference Proceedings (H index 45) in Computer Science & Information Technology (CS & IT) series (Confirmed).

Selected papers from CMLA 2025, after further revisions, will be published in the special issue of the following journals.

Important Dates

Submission Deadline: June 28, 2025 (Final Call)
Authors Notification:July 12, 2025
Final Manuscript Due:July 15, 2025

Co - Located Event

***** The invited talk proposals can be submitted to [email protected]