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Eine Ebene höher- Fakultäten (102029)
- Mathematik, Informatik und Statistik (4808)
- Statistik (2201)
- Lehrstühle/Arbeitsgruppen (635)
- Computationale Statistik (47)
- Lehrstühle/Arbeitsgruppen (635)
- Statistik (2201)
- Mathematik, Informatik und Statistik (4808)
Anzahl der Publikationen auf dieser Ebene: 47
2023
Lebmeier, Elisabeth; Aßenmacher, Matthias und Heumann, Christian
(17. März 2023):
On the Current State of Reproducibility and Reporting of Uncertainty for Aspect-Based Sentiment Analysis.
Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2022, Grenoble, France, September 19--23, 2022, Proceedings, Part II, Grenoble, 19.9.22 - 23.9.22.
S. 537-552
[PDF, 676B]
2022
Goschenhofer, Jann; Ragupathy, Pranav; Heumann, Christian; Bischl, Bernd und Aßenmacher, Matthias
(Dezember 2022):
CC-Top: Constrained Clustering for Dynamic Topic Discovery.
Proceedings of the The First Workshop on Ever Evolving NLP (EvoNLP), Abu Dhabi, UAE, 7.12.22 - 11.12.22.
S. 26-34
[PDF, 1MB]
Rodemann, Julian 
ORCID: https://orcid.org/0000-0001-6112-4136; Fischer, Sebastian; Schneider, Lennart; Nalenz, Malte und Augustin, Thomas
(13. Dezember 2022):
Not All Data Are Created Equal: Lessons From Sampling Theory For Adaptive Machine Learning.
IMS International Conference on Statistics and Data Science (ICSDS), Florenz, December 13, 2022 - December 16, 2022.
[PDF, 1MB]
ORCID: https://orcid.org/0000-0001-6112-4136; Fischer, Sebastian; Schneider, Lennart; Nalenz, Malte und Augustin, Thomas
(13. Dezember 2022):
Not All Data Are Created Equal: Lessons From Sampling Theory For Adaptive Machine Learning.
IMS International Conference on Statistics and Data Science (ICSDS), Florenz, December 13, 2022 - December 16, 2022.
[PDF, 1MB]
2016
Bauer, Nadja; Friedrichs, Klaus; Bischl, Bernd und Weihs, Claus
(2016):
Fast Model Based Optimization of Tone Onset Detection by Instance Sampling.
In: Wilhelm, Adalbert F. X. und Kestler, Hans A. (Hrsg.):
Analysis of Large and Complex Data. Cham: Springer. S. 461-472
Bischl, Bernd; Kerschke, Pascal; Kotthoff, Lars; Lindauer, Marius; Malitsky, Yuri; Frechétte, Alexandre; Hoos, Holger; Hutter, Frank; Leyton-Brown, Kevin; Tierney, Kevin und Vanschoren, Joaquin
(2016):
ASlib: A Benchmark Library for Algorithm Selection.
In: Artificial Intelligence, Bd. 237: S. 41-58
Bischl, Bernd; Kühn, Tobias und Szepannek, Gero
(2016):
On Class Imbalance Correction for Classification Algorithms in Credit Scoring.
In: Lübbecke, Marco (Hrsg.):
Operations Research Proceedings 2014. Cham: Springer International Publishing. S. 37-43
Bischl, Bernd; Lang, Michel; Kotthoff, Lars; Schiffner, Julia; Richter, Jakob; Studerus, Erich; Casalicchio, Giuseppe und Jones, Zachary M.
(2016):
mlr: Machine Learning in R.
In: Journal of Machine Learning Research, Bd. 17, Nr. 1: S. 5938-5942
Degroote, Hans; Bischl, Bernd; Kotthoff, Lars und De Causmaecker, Patrick
(2016):
Reinforcement Learning for Automatic Online Algorithm Selection - an Empirical Study.
16th ITAT Conference Information Technologies - Applications and Theory, Tatranské Matliare, 15.-19. September 2016.
In: Proceedings of the 16th ITAT Conference Information Technologies - Applications and Theory,
S. 93-101
Horn, Daniel; Demircioğlu, Aydin; Bischl, Bernd; Glasmachers, Tobias und Weihs, Claus
(2016):
A Comparative Study on Large Scale Kernelized Support Vector Machines.
In: Advances in Data Analysis and Classification: S. 1-17
Rietzler, Michael; Geiselhart, Florian; Thomas, Janek und Rukzio, Enrico
(2016):
FusionKit: a generic toolkit for skeleton, marker and rigid-body tracking.
8th ACM SIGCHI Symposium on Engineering Interactive Computing Systems, Brüssel, 21.-24. Juni 2016.
In: Proceedings of the 8th ACM SIGCHI Symposium on Engineering Interactive Computing Systems,
S. 73-84
Weihs, Claus; Horn, Daniel und Bischl, Bernd
(2016):
Big data Classification: Aspects on Many Features and Many Observations.
In: Wilhelm, Adalbert F.X. und Kestler, Hans A. (Hrsg.):
Analysis of Large and Complex Data. Cham ; Heidelberg ; New York ; Dordrecht ; London: Springer. S. 113-122
2015
Bischl, Bernd; Lang, Michel; Mersmann, Olaf; Rahnenführer, Jörg und Weihs, Claus
(2015):
BatchJobs and BatchExperiments: Abstraction Mechanisms for Using R in Batch Environments.
In: Journal of Statistical Software, Bd. 64, Nr. 11: S. 1-25
Brockhoff, Dimo; Bischl, Bernd und Wagner, Tobias
(2015):
The Impact of Initial Designs on the Performance of MATSuMoTo on the Noiseless BBOB-2015 Testbed: A Preliminary Study.
Genetic and Evolutionary Computation Conference 2015, Madrid, 11.-15. Juli 2015.
In: GECCO '15 Companion,
Madrid:
Horn, Daniel; Wagner, Tobias; Biermann, Dirk; Weihs, Claus und Bischl, Bernd
(2015):
Model-Based Multi-Objective Optimization: Taxonomy, Multi-Point Proposal, Toolbox and Benchmark.
In: Gaspar-Cunha, António; Henggeler Antunes, Carlos und Coello, Carlos Coello (Hrsg.):
Evolutionary Multi-Criterion Optimization (EMO). 8th International Conference, EMO 2015, Guimarães, Portugal, March 29 - April 1, 2015. Proceedings, Part I. Lecture Notes in Computer Science, Bd. 9018. Berlin: Springer. S. 64-78
Kotthaus, Helena; Korb, Ingo; Lang, Michel; Bischl, Bernd; Rahnenführer, Jörg und Marwedel, Peter
(2015):
Runtime and memory consumption analyses for machine learning R programs.
In: Journal of Statistical Computation and Simulation, Bd. 85, Nr. 1: S. 14-29
Lang, Michel; Kotthaus, Helena; Marwedel, Peter; Weihs, Claus; Rahnenführer, Jörg und Bischl, Bernd
(2015):
Automatic model selection for high-dimensional survival analysis.
In: Journal of Statistical Computation and Simulation, Bd. 85, Nr. 1: S. 62-76
Schmid, Matthias; Kestler, Hans A. und Potapov, Sergej
(2015):
On the validity of time-dependent AUC estimators.
In: Briefings in Bioinformatics, Bd. 16, Nr. 1: S. 153-68
2014
Boulesteix, Anne-Laure und Schmid, Matthias
(2014):
Machine learning versus statistical modeling.
In: Biometrical Journal, Bd. 56, Nr. 4: S. 588-593
Lausser, Ludwig; Schmid, Florian; Schmid, Matthias und Kestler, Hans A.
(2014):
Unlabeling data can improve classification accuracy.
In: Pattern Recognition Letters, Bd. 37: S. 15-23
Mayr, Andreas und Schmid, Matthias
(2014):
Boosting the concordance index for survival data - a unified framework to derive and evaluate biomarker combinations.
In: PLOS ONE 9(1), e84483 [PDF, 442kB]
In: PLOS ONE 9(1), e84483 [PDF, 442kB]
Möst, Lisa; Schmid, Matthias; Faschingbauer, Florian und Hothorn, Torsten
(2014):
Predicting Birth Weight with Conditionally Linear Transformation Models.
In: Statistical Methods in Medical Research
[PDF, 954kB]
Schneeweiß, Hans; Ronning, Gerd und Schmid, Matthias
(2014):
Panel model with multiplicative measurement errors.
In: Beran, Jan; Feng, Yuanhua und Hebbel, Hartmut (Hrsg.):
Empirical Economic and Financial Research - Theory, Methods and Practice. New York: Springer. S. 123-143
Unkel, Steffen; Farrington, Paddy C.; Whitaker, Heather J. und Pebody, Richard
(2014):
Time varying frailty models and the estimation of heterogeneities in transmission of infectious diseases.
In: Journal of the Royal Statistical Society: Series C, Bd. 63, Nr. 1: S. 141-158
2013
Bergmann, Shana; Ziegler, Nina; Bartels, Thomas; Hübel, Jens; Schumacher, Christoph; Rauch, E.; Brandl, S.; Bender, Andreas; Casalicchio, Giuseppe; Krautwald-Junghanns, Maria und Erhard, Michael
(2013):
Prevalence and severity of foot pad alterations in German turkey poults during the early rearing phase.
In: Poultry Science, Bd. 92, Nr. 5: S. 1171-1176
Kreuter, Frauke; Müller, Gerrit und Trappmann, Mark
(2013):
A Note on Mechanisms Leading to Lower Data Quality of Late or Reluctant Respondents.
In: Sociological Methods and Research
2012
Eugster, Manuel J.A.; Hothorn, Torsten und Leisch, Friedrich
(2012):
Domain-based benchmark experiments: Exploratory and inferential analysis.
In: Austrian Journal of Statistics, Bd. 41, Nr. 1: S. 5-26
Mayr, Andreas; Fenske, Nora; Hofner, Benjamin; Kneib, Thomas und Schmid, Matthias
(2012):
Generalized additive models for location scale and shape for high-dimensional data - a flexible approach based on boosting.
In: Journal of the Royal Statistical Society, Series C (Applied Statistics), Bd. 61: S. 403-427
Monecke, Armin und Leisch, Friedrich
(2012):
semPLS: Structural Equation Modeling Using Partial Least Squares.
In: Journal of Statistical Software, Bd. 48: S. 1-32
Schneeweiß, Hans; Rost, Daniel und Schmid, Matthias
(2012):
Probability and quantile estimation from individually micro-aggregated data.
In: Metrika, Bd. 75, Nr. 6: S. 721-742
2011
Dolnicar, Sara; Grün, Bettina und Leisch, Friedrich
(2011):
Quick, simple and reliable: Forced binary survey questions.
In: International Journal of Market Research, Bd. 53, Nr. 2: S. 233-254
Eugster, Manuel J. A.; Knaus, Jochen; Porzelius, Christine; Schmidberger, Markus und Vicedo, E.
(2011):
Hands-on Tutorial for Parallel Computing with R.
In: Computational Statistics, Bd. 26, Nr. 2: S. 219-239
Eugster, Manuel J.A. und Leisch, Friedrich
(2011):
Exploratory Analysis of Benchmark Experiments.
In: Computational Statistics, Bd. 26, Nr. 4: S. 699-710
Eugster, Manuel J.A. und Leisch, Friedrich
(2011):
Weighted and Robust Archetypal Analysis.
In: Computational Statistics and Data Analysis, Bd. 55, Nr. 3: S. 1215-1225
Hothorn, Torsten und Leisch, Friedrich
(2011):
Case studies in reproducibility.
In: Briefings in Bioinformatics, Bd. 12, Nr. 3: S. 288-300
Möller, Teresa; Dolnicar, Sara und Leisch, Friedrich
(2011):
The sustainability-profitability trade-off in tourism: Can it be overcome?
In: Journal of Sustainable Tourism, Bd. 19, Nr. 2: S. 155-169
2010
Dolnicar, Sara und Leisch, Friedrich
(2010):
Evaluation of structure and reproducibility of cluster solutions using the bootstrap.
In: Marketing Letters, Bd. 21, Nr. 1: S. 83-101
Eugster, Manuel J.A. und Leisch, Friedrich
(2010):
Weighted and robust archetypal analysis.
In: Computational Statistics & Data Analysis, Bd. 55, Nr. 3: S. 1215-1225
Leisch, Friedrich
(2010):
Neighborhood graphs, stripes and shadow plots for cluster visualization.
In: Statistics and Computing, Bd. 20, Nr. 4: S. 457-469
Scharl, Teresa; Grün, Bettina und Leisch, Friedrich
(2010):
Mixtures of regression models for time course gene expression data: Evaluation of initialization and random effects.
In: Bioinformatics, Bd. 26, Nr. 3: S. 370-377
Schosser, Alexandra; Fuchs, Karen; Scharl, Teresa; Schloegelhofer, Monika; Kindler, Jochen; Mossaheb, Nilufar; Kaufmann, Rainer M.; Leisch, Friedrich; Kaspar, Siegfried; Sieghart, Werner und Aschauer, Harald N.
(2010):
Interaction between serotonin 5-HT2A receptor gene and dopamine transporter (DAT1) gene polymorphisms influences personality trait of persistence in Austrian caucasians.
In: World Journal of Biological Psychiatry, Bd. 11, Nr. 2: S. 417-424
2009
Absmanner, Evelin; Rouha-Mülleder, Cornelia; Scharl, Teresa; Leisch, Friedrich und Troxler, Josef
(2009):
Effects of different housing systems on the behaviour of beef bulls - An on-farm assessment on Austrian farms.
In: Applied Animal Behaviour Science, Bd. 118: S. 12-19
Dolnicar, Sara; Kaiser, Sebastian; Matus, Katrina und Vialle, Wilma
(2009):
Can Australian universities take measures to increase the lecture attendance of marketing students?
In: Journal of Marketing Education, Bd. 31, Nr. 3: S. 203-211
Eugster, Manuel J.A. und Leisch, Friedrich
(2009):
From Spider-man to Hero - archetypal analysis in R.
In: Journal of Statistical Software, Bd. 30, Nr. 8: S. 1-23
Scharl, Teresa und Leisch, Friedrich
(2009):
gcExplorer: Interactive exploration of gene clusters.
In: Bioinformatics, Bd. 25, Nr. 8: S. 1089-1090
Scharl, Teresa; Striedner, Gerald; Pötschacher, Florentina; Leisch, Friedrich und Bayer, Karl
(2009):
Interactive visualization of clusters in microarray data: An efficient tool for improved metabolic analysis of e. coli.
In: Microbial Cell Factories, Bd. 8, Nr. 37
Scharl, Teresa; Voglhuber, Ingo und Leisch, Friedrich
(2009):
Exploratory and inferential analysis of gene cluster neighborhood graphs.
In: BMC Bioinformatics, Bd. 10, Nr. 1: S. 288
Visne, Ilhami; Dilaveroglu, Erkan; Vierlinger, Clemens; Lauss, Martin; Yildiz, Ahmet; Weinhaeusel, Andreas; Noahammer, Christa; Leisch, Friedrich und Kriegner, Albert
(2009):
RGG: A general GUI framework for R scripts in bioinformatics.
In: BMC Bioinformatics, Bd. 10, Nr. 1: S. 74