![]() | MLDM 2024: 20th International Conference on Machine Learning and Data Mining MLDM 2024 Hotel Dresden, Germany, July 13-18, 2024 |
Conference website | http://www.mldm.de |
Submission link | https://easychair.org/conferences/?conf=mldm2024 |
Abstract registration deadline | January 15, 2024 |
Submission deadline | January 15, 2024 |
The Aim of the Conference
The aim of the conference is to bring together researchers from all over the world who deal with machine learning and data mining in order to discuss the recent status of the research and to direct further developments. Basic research papers as well as application papers are welcome.
Chair
Petra Perner Institute of Computer Vision and applied Computer Sciences IBaI, Germany
Program Committee
- Piotr Artiemjew University of Warmia and Mazury in Olsztyn, Poland
- Sung-Hyuk Cha Pace Universtity, USA
- Ming-Ching Chang University of Albany, USA
- Robert Haralick City University of New York, USA
- Chih-Chung Hsu National Cheng Kung University, Taiwan
- Adam Krzyzak Concordia University, Canada
- Krzysztof Pancerz University Rzeszow, Poland
- Dan Simovici University of Massachusetts Boston, USA
- Tanveer Syeda-Mahmood IBM Almaden Research Center, USA
- Yi Wei Samsung Research America Inc., USA
- Agnieszka Wosiak Lodz University of Technology, Poland
- more to be annouced...
Topics of the conference
Paper submissions should be related but not limited to any of the following topics:
- Association RulesAudio Mining
- Autoamtic Semantic Annotation of Media Content
- Bayesian Models and Methods
- Capability Indices
- Case-Based Reasoning and Associative Memory
- Case-Based Reasoning and Learning
- Classification & Prediction
- classification and interpretation of images, text, video
- Classification and Model Estimation
- ClusteringCognition and Computer Vision
- Conceptional Learning
- conceptional learning and clustering
- Content-Based Image Retrieval
- Control ChartsDecision Trees
- Design of Experiment
- Desirabilities
- Deviation and Novelty Detection
- Feature Grouping, Discretization, Selection and Transformation
- Feature LearningFrequent Pattern Mining
- Goodness measures and evaluaion (e.g. false discovery rates)
- Graph Mining
- 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 in Image Pre-Processing and Segmentation
- Learning in process automationLearning 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 robotsLearning/Adaption of Recognition and Perception
- Mining Financial or Stockmarket Data
- 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 Sequencemining 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 DetectionRetrieval Methods
- Rule Induction and GrammarsSampling methods
- Selection with small samples
- Similarity Measures and Learning of Similarity
- Speech AnalysisStatistical and Conceptual Clustering Methods
- Statistical and Evolutionary LearningStatistical Learning
- Statistical Learning and Neural Net Based Learning
- Strategy of ExperimentationSubspace Methods
- Support Vector MachinesSymbolic Learning and Neural Networks in Document Processing
- TelecommunicationTime Series and Sequential Pattern Mining
- Video MiningVisualization and Data Mining
- Agent Data Mining
- Applications in Medicine
- Applications in Software Testing
- Applications of ClusteringAspects of Data Mining
Paper Submission
The paper must be formatted in the Springer LNCS format. They should have at most 15 pages. The papers will be reviewed by the program committee. The papers will be published in the conference proceedings.https://easychair.org/conferences/?conf=mldm2024Extended versions of the papers will appear in the Special Issue in the Intern. Journal Transaction on Machine Learning and Data Mining or in the Intern. Journal Transaction onCase-Based Reasoning.