7th International Conference on Advanced Machine Learning (AMLA 2026)

7th International Conference on Advanced Machine Learning (AMLA 2026) July 25 ~ 26, 2026, Toronto, Canada https://ais2026.org/amla/index Scope 7th International Conference on Advanced Machine Learning (AMLA 2026) 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 areas of Computer Science, Engineering and Applications. Topics of interest include, but are not limited to, the following  Applications  Learning in knowledge-intensive systems  Learning Methods and analysis  Learning Problems  Trends in ML  Machine Learning Algorithms  Supervised Machine Learning  Unsupervised Machine Learning  Deep Learning  Neural Networks  Reinforcement Learning  Predictive Learning  Learning Problems Paper Submission Authors are invited to submit papers through the conference Submission System by March 28, 2026. 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 AMLA 2026, after further revisions, will be published in the special issue of the following journal.  Machine Learning and Applications: An International Journal (MLAIJ)  International Journal of Artificial Intelligence & Applications (IJAIA) Important Dates • Submission Deadline: March 28, 2026 • Authors Notification: May 23, 2026 • Registration & camera - Ready Paper Due: May 30, 2026 Contact Us Here's where you can reach us: amla@ais2026.org (or) amlaconff@gmail.com Paper Submission Link: https://csit2026.org/submission/index.php