International Conference on Machine Learning Techniques (MLTEC 2020)

Memo

November 21~22, 2020, Zurich, Switzerland https://cst2020.org/mltec/index.html Scope International Conference on Machine Learning Techniques (MLTEC 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Machine Learning Techniques. Topics of interest include, but are not limited to, the following Deep Learning Learning in knowledge-intensive systems Learning Methods and analysis Learning Problems Machine Learning Applications Machine Learning models and applications Machine Learning Recommender systems Machine Translation Neural Networks / Deep Learning ML for NLP Ubiquitous Machine Learning Computer Vision Bayesian Network Data Mining Paper Submission Authors are invited to submit papers through the conference Submission System by November 07, 2020(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 Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed). Selected papers from MLTEC 2020, after further revisions, will be published in the special issue of the following journal. International Journal of Artificial Intelligence & Applications (IJAIA) Machine Learning and Applications: An International Journal (MLAIJ) International Journal of Ubiquitous Computing (IJU) Advances in Vision Computing: An International Journal (AVC) Important Dates Second Batch : (Submissions after September 26, 2020) Submission Deadline:November 07, 2020(Final Call) Authors Notification: November 14, 2020 Registration & camera – Ready Paper Due: November 16, 2020 Contact us Here’s where you can reach us : This email address is being protected from spambots. You need JavaScript enabled to view it. (or) This email address is being protected from spambots. You need JavaScript enabled to view it.