Search results for "Ingo Mierswa"

Hits ?▲	Authors	Title	Venue	Year	Link	Author keywords
1	Ingo Mierswa	Rapid Miner.	KI	2009	DBLP BibTeX RDF
1	Ingo Mierswa	Non-Convex and Multi-Objective Optimization in Data Mining - Non-Convex and Multi-Objective Optimization for Statistical Learning and Numerical Feature Engineering.		2009	RDF
1	Ingo Mierswa	Nichtkonvexe und Multikriterielle Optimierung für Data Mining.	Ausgezeichnete Informatikdissertationen	2009	DBLP BibTeX RDF
1	Ingo Mierswa, Katharina Morik	About the non-convex optimization problem induced by non-positive semidefinite kernel learning.	Adv. Data Analysis and Classification	2008	DBLP DOI BibTeX RDF	JEL Classification C45, C14
1	Christian Bockermann, Ingo Mierswa, Katharina Morik	On the Automated Creation of Understandable Positive Security Models for Web Applications.	PerCom	2008	DBLP DOI BibTeX RDF
1	Christian Bockermann, Ingo Mierswa, Katharina Morik	On the Automated Creation of Understandable Positive Security Models for Web Applications.	LWA	2008	DBLP BibTeX RDF
1	Ingo Mierswa	Controlling overfitting with multi-objective support vector machines.	GECCO	2007	DBLP DOI BibTeX RDF	machine learning, support vector machines, kernel methods, evolution strategies
1	Ingo Mierswa	Regularization through Multi-Objective Optimization.	LWA	2007	DBLP BibTeX RDF
1	Alexander Hinneburg, Ralf Klinkenberg, Ingo Mierswa, Stefan Posch, Steffen Neumann	Workshop on Knowledge Discovery, Data Mining, and Machine Learning and Workshop on Bioinformatics.	LWA	2007	DBLP BibTeX RDF
1	Ingo Mierswa, Michael Wurst	Information preserving multi-objective feature selection for unsupervised learning.	GECCO	2006	DBLP DOI BibTeX RDF	Pareto front segmentation, multi-objective feature selection, unsupervised learning
1	Ingo Mierswa	Evolutionary learning with kernels: a generic solution for large margin problems.	GECCO	2006	DBLP DOI BibTeX RDF	machine learning, support vector machines, kernel methods, evolution strategies, particle swarms
1	Michael Wurst, Katharina Morik, Ingo Mierswa	Localized Alternative Cluster Ensembles for Collaborative Structuring.	ECML	2006	DBLP DOI BibTeX RDF
1	Ingo Mierswa, Michael Wurst	Sound Multi-objective Feature Space Transformation for Clustering.	LWA	2006	DBLP BibTeX RDF
1	Fabian Mörchen, Ingo Mierswa, Alfred Ultsch	Understandable models Of music collections based on exhaustive feature generation with temporal statistics.	KDD	2006	DBLP DOI BibTeX RDF	music mining, logistic regression, meta learning, genre classification, feature generation
1	Ingo Mierswa, Michael Wurst, Ralf Klinkenberg, Martin Scholz, Timm Euler	YALE: rapid prototyping for complex data mining tasks.	KDD	2006	DBLP DOI BibTeX RDF	KDD system, audio and text mining, result visualization, rapid prototyping, distributed data mining, feature construction, data pre-processing, data stream mining, multimedia mining
1	Ingo Mierswa, Katharina Morik	Automatic Feature Extraction for Classifying Audio Data.	Machine Learning	2005	DBLP DOI BibTeX RDF	analysis of audio data, time series transformations, feature extraction, music recommender systems
1	Ingo Mierswa, Katharina Morik	Merkmalsextraktion aus Audiodaten Evolutionäre Aufzucht von Methodenbäumen.	Informatik Spektrum	2005	DBLP DOI BibTeX RDF
1	Helge Homburg, Ingo Mierswa, Bülent Möller, Katharina Morik, Michael Wurst	A Benchmark Dataset for Audio Classification and Clustering.	ISMIR	2005	DBLP BibTeX RDF
1	Ingo Mierswa	Incorporating fuzzy knowledge into fitness: multiobjective evolutionary 3D design of process plants.	GECCO	2005	DBLP DOI BibTeX RDF	evolutionary plant design, fuzzy constraint indexing, multiobjective evolutionary construction
1	Ingo Mierswa, Katharina Morik	Method trees: building blocks for self-organizable representations of value series: how to evolve representations for classifying audio data.	GECCO Workshops	2005	DBLP DOI BibTeX RDF	analysis of audio data, evolving representations, time series transformations, feature extraction
1	Ingo Mierswa, Michael Wurst	Efficient Case Based Feature Construction.	ECML	2005	DBLP DOI BibTeX RDF
1	Ingo Mierswa	Automatic Feature Extraction from Large Time Series.	LWA	2004	DBLP BibTeX RDF
1	Ingo Mierswa	Automatic Feature Extraction from Large Time Series.	GfKl	2004	DBLP DOI BibTeX RDF

Publications of "Ingo Mierswa" ( http://dblp.L3S.de/Authors/Ingo_Mierswa )