ICMLA 2021 : International Conference on Machine Learning and Applications

  in Conferences   Posted on January 4, 2021

Conference Information

Submission Deadline Saturday 03 Jul 2021 Proceedings indexed by :
Conference Dates Dec 13, 2021 - Dec 16, 2021
Conference Address Pasadena, United States
Conference & Submission Link https://www.icmla-conference.org/icmla21/
Conference Organizers : ( Deadline extended ? Click here to edit )

Conference Ranking & Metrics (This is a TOP Conference)

Impact Score 2.97
#Contributing Top Scientists 52
#Papers published by Top Scientists 69
Google Scholar H5-index 30
Guide2Research Overall Ranking: 248
Category Rankings
Image Processing & Computer Vision 37
Machine Learning & Artificial Intelligence 72
Proceedings https://ieeexplore.ieee.org/xpl/conhome/1001544/all-proceedings
DBLP Page https://dblp.uni-trier.de/db/conf/icmla

Conference Call for Papers

Scope of the Conference:
•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
•evolutionary computation
•machine learning and natural language processing
•multi-lingual knowledge acquisition and representation
•grammatical inference
•knowledge discovery in databases
•knowledge Intensive Learning
•machine learning and information retrieval
•machine learning for bioinformatics and computational biology
•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 modelling
•adversarial learning
•machine leaning privacy
•hybrid learning algorithms
•deep learning
•big data
•machine learning in:
o game playing and problem solving
o intelligent virtual environments
o industrial and engineering applications
o homeland security applications
o medicine, bioinformatics and systems biology
o economics, business and forecasting applications

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