21^st IEEE International Conference On Machine Learning and Applications(ICMLA 2022)

December 12-15,2022,Nassau,The Bahamas

Call For Papers

The conference provides a leading international forum for the dissemination of original research in ML, with emphasis on applications as well as novel algorithms and systems. Following the success of previous ICMLA conferences, the conference aims to attract researchers and application developers from a wide range of ML related areas, and the recent emergence of Big Data processing brings an urgent need for machine learning to address these new challenges. The conference will cover both machine learning theoretical research and its applications. Contributions describing machine learning techniques applied to real-world problems and interdisciplinary research involving machine learning, in fields like medicine, biology, industry, manufacturing, security, education, virtual environments, games, are especially encouraged.

Contributions describing applications of machine learning (ML) techniques to real-world problems, interdisciplinary research involving machine learning, experimental and/or theoretical studies yielding new insights into the design of ML systems, and papers describing development of new analytical frameworks that advance practical machine learning methods are especially encouraged.

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

• statistical learning
• neural network learning
• learning through fuzzy logic
• learning through evolution (evolutionary algorithms)
• reinforcement learning
• multi-strategy learning
• cooperative learning
• planning and learning
• multi-agent learning
• online and incremental learning
• scalability of learning algorithms
• inductive learning
• inductive logic programming
• Bayesian networks
• support vector machines
• case-based reasoning
• machine learning for bioinformatics and computational biology
• multi-lingual knowledge acquisition and representation
• grammatical inference
• knowledge acquisition and learning
• knowledge discovery in databases
• knowledge intensive learning
• knowledge representation and reasoning
• machine learning and information retrieval
• machine learning for web navigation and mining
• learning through mobile data mining
• text and multimedia mining through machine learning
• distributed and parallel learning algorithms and applications
• feature extraction and classification
• theories and models for plausible reasoning
• computational learning theory
• cognitive modeling
• hybrid learning algorithms
• medicine, health, bioinformatics and systems biology
• industrial and engineering applications
• security applications
• smart cities

Paper Submission

High quality papers in all Machine Learning areas are solicited. Papers that present new directions in ML will receive careful reviews. Authors are expected to ensure that their final manuscripts are original and are not appearing in other publications. Paper should be limited to 8 pages and submitted in IEEE format (double column). Papers will be reviewed by the Program Committee on the basis of technical quality, originality, significance and clarity. All submissions will be handled electronically. Accepted papers will be published in the conference proceedings, as a hardcopy. Authors of the accepted papers need to present their papers at the conference.

Submit the papers via the Online Submission System.

Important Dates

User Name : Brayden
Posted 21-02-2022 on 23:17:43 AEDT