• Jul 16, 2019 News!Good News! All papers from Volume 9, Number 3 have been indexed by Scopus!   [Click]
  • Mar 27, 2019 News!Good News! All papers from Volume 9, Number 1 have been indexed by Scopus!   [Click]
  • Jul 08, 2019 News!Vol.9, No.4 has been published with online version.   [Click]
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General Information
    • ISSN: 2010-3700 (Online)
    • Abbreviated Title: Int. J. Mach. Learn. Comput.
    • Frequency: Bimonthly
    • DOI: 10.18178/IJMLC
    • Editor-in-Chief: Dr. Lin Huang
    • Executive Editor:  Ms. Cherry L. Chen
    • Abstracing/Indexing: Scopus (since 2017), EI (INSPEC, IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
    • E-mail: ijmlc@ejournal.net
Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.

Upcoming Conference

Conference in 2019





2019 3rd Asia Conference on Machine Learning and Computing will be held in University of Hong Kong, December 7-9, 2019, which is organized by  International Journal of Machine Learning and Computing. It aims to provide a forum for researchers, practitioners, and professionals from the industry, academia and government who are working in the field of machine learning and computing to discourse on research and development, professional practice in related fields.... Learn More





ICMLA 2019 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….. Learn More





The 2019 1st International Conference on Artificial Intelligence and Machine Learning is a non-profit conference. It is organized by IETI and IRIEM and IDSAI and INWASCON and UJ. As one of the leading International symposium, it aims at providing an innovative exchange platform for students, faculties, and researchers from all over the world….. Learn More






With the advent of higher resolution imaging modalities, such as electron microscopy (Cryo-EM, FIB-SEM) and fluorescence superresolution microscopy (SRM), scientists are able to discern subcellular structures at the molecular level leading to discoveries in basic and translational sciences as well as applications in drug discovery and precision medicine. Visualizing cellular, sub-cellular, and protein structures have been recently recognized with Nobel Prizes in Chemistry, for super-resolution fluorescence microscopy in 2014 and for cryo-electron microscopy in 2017. SRM imaging achieves nanometer resolution while cryo-EM allows imaging of structures in their native, frozen, hydrated state by resolving structural details of 1.5 Angstrom. These imaging modalities as well as many others rely on performant computational techniques to reconstruct high resolution images in 2D and 3D for visualization and further quantitative analysis. Advances in machine learning, particularly in deep learning, has a great potential to contribute to high resolution reconstruction process, particularly by improving particle detection and classification steps of reconstruction. 

This second workshop aims to bring the researchers from computational and imaging fields together to have a wider focus on the computational approaches that learn parameters from image data while maintaining an emphasis on the leading edge machine learning methods such as deep learning for all computational tasks: segmentation, classification, construction, and analysis in high resolution imaging modalities (cryo-electron microscopy, FIB-SEM tomography and fluorescence superresolution microscopy)… Learn More



Department of Computer Science and Engineering, Center for AstroInformatics, Modeling and Simulation, PES University and International Astrostatistics Association are proud to present a unique conference on Modeling, Machine Learning and Astronomy.

The Conference aims to set a unique ground as an amalgamation of the diverse ideas and techniques while staying true to the baseline. We expect to discuss new developments in modeling, machine learning, design of complex computer experiments and data analytic techniques which can be used in areas beyond astronomical data analysis. Given the horizontal nature of MMLA, we hope to disseminate methods that are area-agnostic but currently of interest to the broad community of science and engineering.

Topics of interest include, but are not limited to:
• Exoplanets (discovery, machine classification etc.)
• Unsupervised, semi-supervised, and supervised representation learning
• Representation learning for reinforcement learning
• Metric learning and kernel learning
• Deep learning in astronomy
• MCMC on big data
• Statistical Machine Learning
• Bayesian Methods in Astronomy
• Meta-heuristic and Evolutionary Clustering methods and applications in
Astronomy
• Optimization methods
• Swarm intelligence
• Multi-objective optimization
• Dynamical Systems and Complexity
• Information-Theoretic Methods in Life-like Systems
• Predictive Methods for Complex Adaptive Systems and Life-like Systems
Evolutionary Games
Learn More
 



The International Conference on Machine Learning and Data Engineering, 2019 (iCMLDE2019) will gather international and national experts in research topics of Artificial Intelligence (A.I.), Computer Vision, Machine Learning and Data Engineering. A.I. offers timely productivity advances and the conference will cover both applied and theoretical research areas to offer unique opportunities for professional interaction between thinkers, editors, researchers, industrialists, commercial practitioners, SMEs, academic researchers and their students, and identify opportunities for collaborative work.

Conference Tracks: (But not limited to)
=======================================
+ Artificial Intelligence (A. I.)
+ Computer Vision
+ Artificial Neural Networks
+ Pattern Recognition
+ Computer Graphics
+ Motion and Tracking
+ Machine Learning and Deep Learning
+ Cyber Security and Privacy for Big Data
+ Knowledge Discovery, Integration and Transformation
+ Statistical Methods
+ Natural Language Processing
+ High Performance Computing and Scalable Computing
+ Quantum Computing
+ Sensing and Display
+ Biomedical Image Analysis
+ Big Data
+ Data Classification and Regression
+ Data and Image Compression
+ Robotics
+ Information Retrieval and Social Media
+ Data Warehouse, Clustering and Visualization
+ Finance Machine Learning and Data Engineering

Learn More
 




The Australasian Data Mining Conference has established itself as the premier Australasian meeting for both practitioners and researchers in data mining. It is devoted to the art and science of intelligent analysis of (usually big) data sets for meaningful (and previously unknown) insights. This conference will enable the sharing and learning of research and progress in the local context and new breakthroughs in data mining algorithms and their applications across all industries.
 
AusDM invites contributions addressing current research in data mining and knowledge discovery as well as experiences, novel applications and future challenges. Topics of interest include, but are not restricted to:

- Applications and Case Studies — Lessons and Experiences
- Big Data Analytics
- Biomedical and Health Data Mining
- Business Analytics
- Computational Aspects of Data Mining
- Data Integration, Matching and Linkage
- Data Mining in Education
- Data Mining in Security and Surveillance
- Data Preparation, Cleaning and Preprocessing
- Data Stream Mining
- Evaluation of Results and their Communication
- Implementations of Data Mining in Industry
- Integrating Domain Knowledge
- Link, Tree, Graph, Network and Process Mining
- Multimedia Data Mining
- New Data Mining Algorithms
- Professional Challenges in Data Mining
- Privacy-preserving Data Mining
- Spatial and Temporal Data Mining
- Text Mining
- Visual Analytics
- Web and Social Network Mining
Learn More

 

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E-mail: ijmlc@ejournal.net