Call for Papers
17th International Conference on Machine Learning and Data Mining
MLDM´2021
www.mldm.de July 17 - 22, 2021 New York, USA

Chair
Petra Perner
FutureLab Artificial Intelligence_IBaI_II
Institute of Computer Vision and applied Computer Sciences, IBaI

Program Committee
Reneta Barneva The State University of New York at Fredonia, USA
Sung-Hyuk Cha Pace University, USA
Ireneusz Czarnowski Gdynia Maritime University, Poland
Roberto Corrizo Universtiy of Bari, Italy
Christoph F. Eick Universtiy of Houston, USA
Mark J. Embrechts Rensselaer Polytechnic Institute and CardioMag Imaging, Inc, USA
Ana Fred Technical University of Lisboa, Portugal
Giorgio Giacinto University of Cagliari, Italy
Aminata Kane Concordia University, Canada
Piet Kommers University of Twente, The Netherlands
Olga Krasotkina Russian Stae University, Russia
Dimitris Karras Chalkis Institute of Technology, Greece
Adam Krzyzak Concordia University, Canada
Valerio Pascucci University of Utah, USA
Gianvito Pio University of Bari, Italy
Lyndon Smith University of the West of England, UK
Francis E.H. Tay National University of Singapore, Singapore
Turki Turki King Abdulaziz University, Saudi Arabia
Zeev Volkovich ORT Braude College of Engineering, Israel
Patrick Wang Northeastern University, USA

Aim of the Conference
The MLDM´2021 conference is the fourteenth event in a series of Machine Learning and Data Mining meetings. The aim of MLDM is to bring together from all over the world researchers dealing with machine learning and data mining, in order to discuss the recent status of the research in the field and to direct its further developments.
Basic research papers as well as application papers are welcome. All kinds of applications are welcome, but special preference will be given to multimedia related applications, biomedical applications, and webmining. Paper submissions should be related but not limited to any of the following topics:


• Applications in Medicine
• Applications of Clustering
• Aspects of Data Mining
• Association Rules
• Audio Mining
• Autoamtic Semantic Annotation of Media Content
• Bayesian Models and Methods
• Case-Based Reasoning and Associative Memory
• case-based reasoning and learning
• classification and interpretation of images, text, video
• Classification and Model Estimation
• Cognition and Computer Vision
• conceptional learning and clustering
• Content-Based Image Retrieval
• Decision Trees
• Deviation and Novelty Detection
• Feature Grouping, Discretization, Selection and Transformation
• Feature Learning
• Frequent Pattern Mining
• Goodness measures and evaluaion (e.g. false discovery rates)
• High-Content Analysis of Microscopic Images in Medicine, Biotechnology and Chemistry
• inductive learning including decision tree and rule induction learning
• knowledge extraction from text, video, signals, and images
• Learning and adaptive control
• Learning for Handwriting Recognition
• Learning for robots
• Learning in Image Pre-Processing and Segmentation
• Learning in process automation
• Learning of action patterns
• Learning of appropriate behaviour
• Learning of internal representations and models
• Learning of Ontologies
• Learning of Semantic Inferencing Rules
• Learning of Visual Ontologies
• Learning/adaption of recognition and perception
• mining gene data bases and biological data bases
• Mining Images and Texture
• Mining Images in Computer Vision
• mining images, temporal-spatial data, images from remote sensing
• Mining Motion from Sequence
• Mining Social Media
• mining structural representations such as log files, text documents and HTML documents
• mining text documents
• Network Analysis and Intrusion Detection
• Neural Methods
• Nonlinear Function Learning and Neural Net-Based Learning
• organisational learning and evolutional learning
• probabilistic information retrieval
• Real-Time Event Learning and Detection
• Retrieval Methods
• Rule Induction and Grammars
• Sampling methods
• Selection bias
• Selection with small samples
• similarity
• similarity measures and learning
• Speech Analysis
• Statistical and Conceptual Clustering Methods: Basics
• Statistical and Evolutionary Learning
• statistical learning and neural net-based learning
• Subspace Methods
• Support Vector Machines
• Symbolic Learning and Neural Networks in Document Processing
• Time Series and Sequential Pattern Mining
• video mining
• visualization and data mining

Important Dates
Deadline for paper submission: January 15, 2021
Notification of acceptance: March 18, 2021 Submission of camera-ready copy: April 05, 2021

Paper submission
Please submit the electronic version of your camera-ready paper through the conference management system (http://www.easychair.org/). If you have any problems with the system please do not hesitate to contact info@mldm.de.
Papers must be formatted in the Springer LNCS format. They should have at most 15 pages. Papers will be reviewed by the program committee. Accepted long papers will appear in the proceedings book "Machine Learning and Data Mining in Pattern Recognition". The proceedings book will be published as OPEN-ACCESS book. The book can read everybody in the world. Extended versions of selected papers will be published in a special issue of an international journal after the conference.

Tutorials
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Tutorial Standardization in Immunoflourescence
Prof. Dr. Petra Perner, Institute of Computer Vision and Applied Computer Sciences IBaI,
http://www.mda-signals.de/t_stand.php

Data Mining Tutorial
Prof. Dr. Petra Perner, Institute of Computer Vision and Applied Computer Sciences IBaI,
http://www.data-mining-forum.de/t_dm.php

Case-Based Reasoning Tutorial
Prof. Dr. Petra Perner, Institute of Computer Vision and Applied Computer Sciences IBaI,
http://www.data-mining-forum.de/t_cbr.php

Intelligent Image Interpretation and Computer Vision in Medicine, Biotechnology, Chemistry & Food Industry
Prof. Dr. Petra Perner, Institute of Computer Vision and Applied Computer Sciences IBaI
http://www.data-mining-forum.de/t_iicv.php


Workshops (http://www.data-mining-forum.de/workshops.php)
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* Workshop I-Business to Manufacturing and LifeScience B2ML 2021
* Workshop on Data Mining in Marketing DMM 2021
* International Workshop Case-Based Reasoning CBR-AI&PR 2021
* Intern. Workshop on Multimedia Forensic Data Analysis Forensic 2021

Exhibition
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18th Industrial Exhibition on Intelligent Data and Image Analysis IEDA 2021
We like to invite you to present your company or publishing house at the Industrial Exhibition IEDA 2021
(www.iedaexhibition.de).