18th International Conference on Machine Learning and Data Mining MLDM 2022

Memo

The MLDM conference this year is one of the conferences in a series of MLDM events that have been originally started out as a workshop in 1999. Researcher and Industrial People from different fields will present theoretical aspects and their applications, and the results obtained by applying data mining. Besides that, newcomers in the field can get a fast introduction to Data Mining by taking the tutorial running in connection with the conference. In a special industry session practicioners from different industrial branches can present their ongoing projects and discuss their work with the auditorium. An industrial exhibition, where companies are able to present their data-mining tools or applications including data-mining procedures will round up the conference. The Problem and Solution hour will give you the opportunity to present your application and ask for support by researchers. Meet up at the social event will give you the opportunity to compare notes with top leading researchers in Data Mining and Machine Learning from all over the world. Target groups of MLDMResearchers and PhD studentsResearchers doing theoretical and applied research in data mining and machine learning in pattern recognition. PracticionersPracticioners from different industrial, social or economic branches interested in ground breaking developments in the field of machine learning and data mining.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. All kinds of applications are welcome but special preference will be given to multimedia related applications, applications from live sciences and webmining. Paper submissions should be related but not limited to any of the following topics: association rulescase-based reasoning and learningclassification and interpretation of images, text, videoconceptional learning and clusteringGoodness measures and evaluaion (e.g. false discovery rates)inductive learning including decision tree and rule induction learningknowledge extraction from text, video, signals and imagesmining gene data bases and biological data basesmining images, temporal-spatial data, images from remote sensingmining structural representations such as log files, text documents and HTML documentsmining text documentsorganisational learning and evolutional learningprobabilistic information retrievalSampling methodsSelection with small samplessimilarity measures and learning of similaritystatistical learning and neural net based learningvideo miningvisualization and data miningApplications of ClusteringAspects of Data MiningApplications in MedicineAutoamtic Semantic Annotation of Media ContentBayesian Models and MethodsCase-Based Reasoning and Associative MemoryClassification and Model EstimationContent-Based Image RetrievalDecision TreesDeviation and Novelty DetectionFeature Grouping, Discretization, Selection and TransformationFeature LearningFrequent Pattern MiningHigh-Content Analysis of Microscopic Images in Medicine, Biotechnology and ChemistryLearning and adaptive controlLearning/adaption of recognition and perceptionLearning for Handwriting RecognitionLearning in Image Pre-Processing and SegmentationLearning in process automationLearning of internal representations and modelsLearning of appropriate behaviourLearning of action patternsLearning of OntologiesLearning of Semantic Inferencing RulesLearning of Visual OntologiesLearning robotsMining Images in Computer VisionMining Images and TextureMining Motion from SequenceNeural MethodsNetwork Analysis and Intrusion DetectionNonlinear Function Learning and Neural Net Based LearningReal-Time Event Learning and DetectionRetrieval MethodsRule Induction and GrammarsSpeech AnalysisStatistical and Conceptual Clustering MethodsStatistical and Evolutionary LearningSubspace MethodsSupport Vector MachinesSymbolic Learning and Neural Networks in Document ProcessingTime Series and Sequential Pattern MiningAudio MiningCognition and Computer VisionClusteringClassification and PredictionStatistical LearningAssociation RulesTelecommunicationDesign of ExperimentStrategy of ExperimentationCapability IndicesDeviation and Novelty DetectionControl ChartsDesign of ExperimentsCapability IndicesConceptional LearningGoodness Measures and Evaluation (e.g. false discovery rates)Inductive Learning Including Decision Tree and Rule Induction LearningOrganisational Learning and Evolutional LearningSampling MethodsSimilarity Measures and Learning of SimilarityStatistical Learning and Neural Net Based LearningVisualizationFor further information please visit: www.mldm.de.   Tickets: https://go.evvnt.com/813228-2?pid=5569  Date and Time: On Sat, Jul 16, 2022 at (9:00 AM) - Thu, Jul 21, 2022 at (5:00 PM) Venue details: New York Marriott Downtown, 85 West Street At Albany Street, New York, NY, 10006, United States Price:General Admission: EUR 550.00