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MLSC 2020 - International Conference on Machine Learning and Soft Computing (MLSC 2020)

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Website https://acsty2020.org/mlsc/index.html | Edit Freely

Category Machine Learning; Clustering; Hybrid learning algorithms; Inductive logic programming; Machine learning and information retrieval; Probabilistic networks; Reinforcement learning; Visualization of patterns in data; Soft Computing; Data Mining & Information Retrieval; Fuzzy, Stochastic and Probabilistic computing; Perception Based Intelligent Decision Systems; Advanced Soft Computing and Multi-Objective Evolutionary Computing

Deadline: December 14, 2019 | Date: April 25, 2020-April 26, 2020

Venue/Country: Copenhagen, Denmark, Denmark

Updated: 2019-12-09 19:27:33 (GMT+9)

Call For Papers - CFP

April 25 ~ 26, 2020, Copenhagen, Denmark

https://acsty2020.org/mlsc/index.html

Scope

International Conference on Machine Learning and Soft Computing (MLSC 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications Machine learning and Soft Computing. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.

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 Machine learning, Soft Computing and applications.

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

Machine Learning

Analogical learning methods

Automated knowledge acquisition

Case based methodsv

Clustering

Connectionist networks

Ensemble methods

Evolution based methods

Explanation based learning

Hybrid learning algorithms

Inductive logic programming

Learning decision

Learning from instruction

Learning in integrated architectures

Machine learning and information retrieval

Machine learning and natural language processing

Machine learning Applications

Multi strategy, Multi agent learning

Probabilistic networks

Regression trees

Reinforcement learning

Statistical models

Visualization of patterns in data

Soft Computing

Data Mining & Information Retrieval

Data mining for Social Network Data

Expert Systems

Fuzzy, Stochastic and Probabilistic computing

Intelligent Software Agent Systems and Architectures

Intelligent Systems

Morphic Computing

Multi objective optimization

Neural computing

Pattern recognition

Perception Based Intelligent Decision Systems

Soft Computing and Agents

Soft Computing and Pattern Recognition

Soft Computing Applications

Soft Computing for Big Data

Soft Computing Fundamental and Optimization

Soft Computing in Bio-mimetic Pattern Recognition

Soft Computing in Computer Graphics, Animation

Soft Computing Modeling for Perception and Intelligence

Advanced Soft Computing and Multi-Objective Evolutionary Computing

Paper Submission

Authors are invited to submit papers through the conference Submission System by December 14, 2019. 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 MLSC 2020, after further revisions, will be published in the special issue of the following journal.

Machine Learning and Applications: An International Journal (MLAIJ)

International Journal on Soft Computing (IJSC)

Information Technology in Industry (ITII)New - ESCI Indexed

Important Dates

Submission Deadline : December 14, 2019

Authors Notification : January 26, 2020

Registration & camera - Ready Paper Due : February 08, 2020

Contact Us

Here's where you can reach us : mlsc@acsty2020.org (or) mlscconf@yahoo.com


Keywords: Accepted papers list. Acceptance Rate. EI Compendex. Engineering Index. ISTP index. ISI index. Impact Factor.
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