ICMLA 2023 - CFP
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CALL FOR PAPERS
ICMLA 2023
The 22nd International Conference on Machine Learning and Applications
Website link: https://www.icmla-conference.org/icmla23/index.php
December 15-17, 2023, Jacksonville, Florida
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Important Dates:
Special Sessions/Tutorial/Challenge Proposals
Submission Deadline: May 1, 2023
Notification of Acceptance: May 15, 2023
Main Conference Papers
Submission Deadline: July 15, 2023
Notification of Acceptance: August 15, 2023
Special Sessions Papers
Submission Deadline: August 20, 2023
Notification of Acceptance: September 20, 2023
Camera Ready Papers
Main Conference: September 15, 2023
Special Sessions: September 30, 2023
Pre-registration: October 15, 2023
Conference: December 15-17, 2023
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Call for Papers
ICMLA 2023 aims to bring together researchers and practitioners to present their latest achievements and innovations in the area of machine learning (ML).
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.
The technical program will consist of, but is not limited to, the following topics of interest:
- 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
- deep and transfer learning
- federated learning
- machine learning on the edge
- machine learning for computer vision
- hybrid learning algorithms
Applications of machine learning in:
- medicine, health, bioinformatics and systems biology
- industrial and engineering applications
- security applications
- smart cities and autonomous driving
- game playing and problem solving
- intelligent virtual environments
- economics, business and forecasting applications, etc.
The conference will include a number of interesting keynote plenary talks, which will be announced on the conference web site as arrangements are finalized. Previous invited speakers included numerous fellows of AMLA, AMIA, AAAS, AAAI, etc.
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. A selected number of accepted papers will be invited for possible inclusion, in an expanded and revised form, in some journal special issues.
ICMLA'23 Best Paper Award and ICMLA'23 Best Poster Award will be conferred at the conference to the authors of the best research paper and best poster presentation, respectively, based on the reviewers and Program Committee recommendations.
Detailed instructions for submitting papers can be found at