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2020 – today
- 2024
[j58]Gianna Serafina Monti
, Peter Filzmoser:
A robust knockoff filter for sparse regression analysis of microbiome compositional data. Comput. Stat. 39(1): 271-288 (2024)- [j57]Claudia Cappello, Nikolaus Piccolotto, Christoph Muehlmann, Markus Bögl, Peter Filzmoser, Silvia Miksch, Klaus Nordhausen:
Visual Interactive Parameter Selection for Temporal Blind Source Separation. J. Data Sci. Stat. Vis. 4(3) (2024) - [j56]Anna-Christina Glock, Florian Sobieczky, Johannes Fürnkranz, Peter Filzmoser, Martin Jech:
Predictive change point detection for heterogeneous data. Neural Comput. Appl. 36(26): 16071-16096 (2024) - [j55]Nikolaus Piccolotto, Markus Bögl, Christoph Muehlmann, Klaus Nordhausen, Peter Filzmoser, Johanna Schmidt, Silvia Miksch:
Data Type Agnostic Visual Sensitivity Analysis. IEEE Trans. Vis. Comput. Graph. 30(1): 1106-1116 (2024) - 2023
- [j54]Fatma Sevinç Kurnaz, Peter Filzmoser:
Robust and sparse multinomial regression in high dimensions. Data Min. Knowl. Discov. 37(4): 1609-1629 (2023) - [j53]Fatma Sevinç Kurnaz, Peter Filzmoser:
enetLTS: Robust and Sparse Methods for High Dimensional Linear, Binary, and Multinomial Regression. J. Open Source Softw. 8(82): 4773 (2023) - [j52]Christopher Rieser, Peter Filzmoser:
Extending compositional data analysis from a graph signal processing perspective. J. Multivar. Anal. 198: 105209 (2023) - [i7]Anna-Christina Glock, Florian Sobieczky, Johannes Fürnkranz, Peter Filzmoser, Martin Jech:
Predictive change point detection for heterogeneous data. CoRR abs/2305.06630 (2023) - [i6]Nikolaus Piccolotto, Markus Bögl, Christoph Muehlmann, Klaus Nordhausen, Peter Filzmoser, Johanna Schmidt, Silvia Miksch:
Data Type Agnostic Visual Sensitivity Analysis. CoRR abs/2309.03580 (2023) - 2022
- [j51]Gianna Serafina Monti, Peter Filzmoser:
Robust logistic zero-sum regression for microbiome compositional data. Adv. Data Anal. Classif. 16(2): 301-324 (2022) - [j50]Nikolaus Piccolotto, Markus Bögl, Christoph Muehlmann, Klaus Nordhausen, Peter Filzmoser, Silvia Miksch:
Visual Parameter Selection for Spatial Blind Source Separation. Comput. Graph. Forum 41(3): 157-168 (2022) - [j49]Nikolaus Piccolotto, Markus Bögl, Theresia Gschwandtner, Christoph Muehlmann, Klaus Nordhausen, Peter Filzmoser, Silvia Miksch:
TBSSvis: Visual analytics for Temporal Blind Source Separation. Vis. Informatics 6(4): 51-66 (2022) - [p1]Peter Filzmoser, Alexandra Mazak-Huemer:
Massive Data Sets - Is Data Quality Still an Issue? Digital Transformation 2022: 269-279 - [i5]Christopher Rieser, Peter Filzmoser:
Extending compositional data analysis from a graph signal processing perspective. CoRR abs/2201.10610 (2022) - [i4]Georg Heiler, Thassilo Gadermaier, Thomas Haider, Allan Hanbury, Peter Filzmoser:
Identifying the root cause of cable network problems with machine learning. CoRR abs/2203.06989 (2022) - 2021
- [j48]Nikola Stefelová, Andreas Alfons, Javier Palarea-Albaladejo, Peter Filzmoser, Karel Hron:
Robust regression with compositional covariates including cellwise outliers. Adv. Data Anal. Classif. 15(4): 869-909 (2021) - [j47]Gianna Serafina Monti, Peter Filzmoser:
Sparse least trimmed squares regression with compositional covariates for high-dimensional data. Bioinform. 37(21): 3805-3814 (2021) - [j46]António Pedro Duarte Silva, Paula Brito, Peter Filzmoser, José G. Dias:
MAINT.Data: Modelling and Analysing Interval Data in R. R J. 13(2): 266 (2021) - [j45]Sara de la Rosa de Sáa, María Asunción Lubiano, Beatriz Sinova, María Ángeles Gil, Peter Filzmoser:
Location-Free Robust Scale Estimates for Fuzzy Data. IEEE Trans. Fuzzy Syst. 29(6): 1682-1694 (2021) - [i3]Nikolaus Piccolotto, Markus Bögl, Christoph Muehlmann, Klaus Nordhausen, Peter Filzmoser, Silvia Miksch:
Visual Parameter Selection for Spatial Blind Source Separation. CoRR abs/2112.08888 (2021) - 2020
- [j44]Peter Filzmoser, Sebastiaan Höppner, Irene Ortner, Sven Serneels, Tim Verdonck:
Cellwise robust M regression. Comput. Stat. Data Anal. 147: 106944 (2020) - [j43]Irene Ortner, Peter Filzmoser, Christophe Croux:
Robust and sparse multigroup classification by the optimal scoring approach. Data Min. Knowl. Discov. 34(3): 723-741 (2020) - [j42]Dominika Miksová, Peter Filzmoser, Maarit Middleton:
Imputation of values above an upper detection limit in compositional data. Comput. Geosci. 136: 104383 (2020) - [i2]Nikolaus Piccolotto, Markus Bögl, Theresia Gschwandtner, Christoph Muehlmann, Klaus Nordhausen, Peter Filzmoser, Silvia Miksch:
TBSSvis: Visual Analytics for Temporal Blind Source Separation. CoRR abs/2011.09896 (2020)
2010 – 2019
- 2019
- [j41]Sárka Brodinová, Peter Filzmoser, Thomas Ortner, Christian Breiteneder, Maia Rohm:
Robust and sparse k-means clustering for high-dimensional data. Adv. Data Anal. Classif. 13(4): 905-932 (2019) - [j40]Caterina Gozzi, Peter Filzmoser, Antonella Buccianti, Orlando Vaselli, Barbara Nisi:
Statistical methods for the geochemical characterisation of surface waters: The case study of the Tiber River basin (Central Italy). Comput. Geosci. 131: 80-88 (2019) - [c22]Alexander Wurl, Andreas A. Falkner, Alois Haselböck, Alexandra Mazak, Peter Filzmoser:
Exploring Robustness in a Combined Feature Selection Approach. DATA 2019: 84-91 - [i1]Alexander Dür, Peter Filzmoser, Andreas Rauber:
Inspecting the Behaviour of Deep Learning Neural Networks. ERCIM News 2019(116) (2019) - 2018
- [j39]Sárka Brodinová, Maia Zaharieva, Peter Filzmoser, Thomas Ortner, Christian Breiteneder:
Clustering of imbalanced high-dimensional media data. Adv. Data Anal. Classif. 12(2): 261-284 (2018) - [j38]António Pedro Duarte Silva, Peter Filzmoser, Paula Brito:
Outlier detection in interval data. Adv. Data Anal. Classif. 12(3): 785-822 (2018) - [j37]Max Landauer, Markus Wurzenberger, Florian Skopik, Giuseppe Settanni, Peter Filzmoser:
Dynamic log file analysis: An unsupervised cluster evolution approach for anomaly detection. Comput. Secur. 79: 94-116 (2018) - [j36]Peter Filzmoser, Fatma Sevinç Kurnaz:
A robust Liu regression estimator. Commun. Stat. Simul. Comput. 47(2): 432-443 (2018) - [j35]Sonia Pérez-Fernández, Pablo Martínez-Camblor, Peter Filzmoser, Norberto Corral:
nsROC: An R package for Non-Standard ROC Curve Analysis. R J. 10(2): 55 (2018) - [j34]Arthur Zimek, Peter Filzmoser:
There and back again: Outlier detection between statistical reasoning and data mining algorithms. WIREs Data Mining Knowl. Discov. 8(6) (2018) - [c21]Alexander Wurl, Andreas A. Falkner, Peter Filzmoser, Alois Haselböck, Alexandra Mazak, Simon Sperl:
A Comprehensive Prediction Approach for Hardware Asset Management. DATA (Revised Selected Papers) 2018: 26-49 - [c20]Alexander Dür, Andreas Rauber, Peter Filzmoser:
Reproducing a Neural Question Answering Architecture Applied to the SQuAD Benchmark Dataset: Challenges and Lessons Learned. ECIR 2018: 102-113 - [c19]Max Landauer, Markus Wurzenberger, Florian Skopik, Giuseppe Settanni, Peter Filzmoser:
Time Series Analysis: Unsupervised Anomaly Detection Beyond Outlier Detection. ISPEC 2018: 19-36 - 2017
- [j33]Karel Hron, Paula Brito, Peter Filzmoser:
Exploratory data analysis for interval compositional data. Adv. Data Anal. Classif. 11(2): 223-241 (2017) - [j32]Sara de la Rosa de Sáa, María Asunción Lubiano, Beatriz Sinova, Peter Filzmoser:
Robust scale estimators for fuzzy data. Adv. Data Anal. Classif. 11(4): 731-758 (2017) - [j31]Viktor Vad, Douglas Cedrim, Wolfgang Busch, Peter Filzmoser, Ivan Viola:
Generalized box-plot for root growth ensembles. BMC Bioinform. 18(S-2): 65:1-65:15 (2017) - [j30]Markus Bögl, Peter Filzmoser, Theresia Gschwandtner, Tim Lammarsch, Roger A. Leite, Silvia Miksch, Alexander Rind:
Cycle Plot Revisited: Multivariate Outlier Detection Using a Distance-Based Abstraction. Comput. Graph. Forum 36(3): 227-238 (2017) - [c18]László Grad-Gyenge, Attila Kiss, Peter Filzmoser:
Graph Embedding Based Recommendation Techniques on the Knowledge Graph. UMAP (Adjunct Publication) 2017: 354-359 - 2016
- [j29]Karel Hron, Alessandra Menafoglio, Matthias Templ, Klara Hruzová, Peter Filzmoser:
Simplicial principal component analysis for density functions in Bayes spaces. Comput. Stat. Data Anal. 94: 330-350 (2016) - [c17]László Grad-Gyenge, Peter Filzmoser:
The Paradigm of Relatedness. BIS (Workshops) 2016: 57-68 - 2015
- [c16]Markus Bögl, Peter Filzmoser, Theresia Gschwandtner, Silvia Miksch, Wolfgang Aigner, Alexander Rind, Tim Lammarsch:
Visually and statistically guided imputation of missing values in univariate seasonal time series. VAST 2015: 189-190 - [c15]Markus Bögl, Wolfgang Aigner, Peter Filzmoser, Theresia Gschwandtner, Tim Lammarsch, Silvia Miksch, Alexander Rind:
Integrating Predictions in Time Series Model Selection. EuroVA@EuroVis 2015: 73-77 - 2014
- [j28]Peter Filzmoser, Cristian Gatu, Achim Zeileis:
Special issue on statistical algorithms and software in R. Comput. Stat. Data Anal. 71: 887-888 (2014) - [c14]Sara de la Rosa de Sáa, Peter Filzmoser, María Ángeles Gil, María Asunción Lubiano:
On the Robustness of Absolute Deviations with Fuzzy Data. SMPS 2014: 133-141 - 2013
- [j27]Peter Filzmoser, Valentin Todorov:
Robust tools for the imperfect world. Inf. Sci. 245: 4-20 (2013) - [j26]Klaudius Kalcher, Roland N. Boubela, Wolfgang Huf, Bharat B. Biswal, Pia Baldinger, Uta Sailer, Peter Filzmoser, Siegfried Kasper, Claus Lamm, Rupert Lanzenberger, Ewald Moser, Christian Windischberger:
RESCALE: Voxel-specific task-fMRI scaling using resting state fluctuation amplitude. NeuroImage 70: 80-88 (2013) - [j25]Christophe Croux, Peter Filzmoser, Heinrich Fritz:
Robust Sparse Principal Component Analysis. Technometrics 55(2): 202-214 (2013) - [j24]Markus Bögl, Wolfgang Aigner, Peter Filzmoser, Tim Lammarsch, Silvia Miksch, Alexander Rind:
Visual Analytics for Model Selection in Time Series Analysis. IEEE Trans. Vis. Comput. Graph. 19(12): 2237-2246 (2013) - 2012
- [j23]Matthias Templ, Andreas Alfons, Peter Filzmoser:
Exploring incomplete data using visualization techniques. Adv. Data Anal. Classif. 6(1): 29-47 (2012) - [j22]N. M. Neykov, Peter Filzmoser, P. N. Neytchev:
Robust joint modeling of mean and dispersion through trimming. Comput. Stat. Data Anal. 56(1): 34-48 (2012) - [j21]N. M. Neykov, Pavel Cízek, Peter Filzmoser, P. N. Neytchev:
The least trimmed quantile regression. Comput. Stat. Data Anal. 56(6): 1757-1770 (2012) - [j20]Josep-Antoni Martín-Fernández, Karel Hron, Matthias Templ, Peter Filzmoser, Javier Palarea-Albaladejo:
Model-based replacement of rounded zeros in compositional data: Classical and robust approaches. Comput. Stat. Data Anal. 56(9): 2688-2704 (2012) - [j19]Heinrich Fritz, Peter Filzmoser, Christophe Croux:
A comparison of algorithms for the multivariate L 1-median. Comput. Stat. 27(3): 393-410 (2012) - [j18]Peter Filzmoser, Karel Hron, Matthias Templ:
Discriminant analysis for compositional data and robust parameter estimation. Comput. Stat. 27(4): 585-604 (2012) - [j17]Peter Filzmoser, Karel Hron, Clemens Reimann:
Interpretation of multivariate outliers for compositional data. Comput. Geosci. 39: 77-85 (2012) - [c13]Johannes Kehrer, Roland N. Boubela, Peter Filzmoser, Harald Piringer:
A generic model for the integration of interactive visualization and statistical computing using R. IEEE VAST 2012: 233-234 - [c12]Cláudia Pascoal, Maria Rosário de Oliveira, Rui Valadas, Peter Filzmoser, Paulo Salvador, António Pacheco:
Robust feature selection and robust PCA for internet traffic anomaly detection. INFOCOM 2012: 1755-1763 - [c11]Moritz Gschwandtner, Peter Filzmoser:
Outlier Detection in High Dimension Using Regularization. SMPS 2012: 237-244 - [c10]Karel Hron, Peter Filzmoser:
Robust Diagnostics of Fuzzy Clustering Results Using the Compositional Approach. SMPS 2012: 245-253 - [c9]Valentin Todorov, Peter Filzmoser:
Comparing Classical and Robust Sparse PCA. SMPS 2012: 283-291 - 2011
- [j16]Valentin Todorov, Matthias Templ, Peter Filzmoser:
Detection of multivariate outliers in business survey data with incomplete information. Adv. Data Anal. Classif. 5(1): 37-56 (2011) - [j15]Wolfgang Berger, Harald Piringer, Peter Filzmoser, M. Eduard Gröller:
Uncertainty-Aware Exploration of Continuous Parameter Spaces Using Multivariate Prediction. Comput. Graph. Forum 30(3): 911-920 (2011) - [j14]Matthias Templ, Alexander Kowarik, Peter Filzmoser:
Iterative stepwise regression imputation using standard and robust methods. Comput. Stat. Data Anal. 55(10): 2793-2806 (2011) - [j13]Andreas Alfons, Wolfgang E. Baaske, Peter Filzmoser, Wolfgang Mader, Roland Wieser:
Robust variable selection with application to quality of life research. Stat. Methods Appl. 20(1): 65-82 (2011) - [j12]Andreas Alfons, Stefan Kraft, Matthias Templ, Peter Filzmoser:
Simulation of close-to-reality population data for household surveys with application to EU-SILC. Stat. Methods Appl. 20(3): 383-407 (2011) - [j11]Cagatay Turkay, Peter Filzmoser, Helwig Hauser:
Brushing Dimensions - A Dual Visual Analysis Model for High-Dimensional Data. IEEE Trans. Vis. Comput. Graph. 17(12): 2591-2599 (2011) - [c8]Horst Treiblmaier, Peter Filzmoser:
Benefits from Using Continuous Rating Scales in Online Survey Research. ICIS 2011 - 2010
- [j10]Johannes Kehrer, Peter Filzmoser, Helwig Hauser:
Brushing Moments in Interactive Visual Analysis. Comput. Graph. Forum 29(3): 813-822 (2010) - [j9]Valentin Todorov, Peter Filzmoser:
Robust statistic for the one-way MANOVA. Comput. Stat. Data Anal. 54(1): 37-48 (2010) - [j8]Karel Hron, Matthias Templ, Peter Filzmoser:
Imputation of missing values for compositional data using classical and robust methods. Comput. Stat. Data Anal. 54(12): 3095-3107 (2010) - [j7]Horst Treiblmaier, Peter Filzmoser:
Exploratory factor analysis revisited: How robust methods support the detection of hidden multivariate data structures in IS research. Inf. Manag. 47(4): 197-207 (2010) - [c7]Peter Filzmoser, Karel Hron:
Robust Methods for Compositional Data. COMPSTAT 2010: 79-88 - [c6]Andreas Alfons, Matthias Templ, Peter Filzmoser, Josef Holzer:
A Comparison of Robust Methods for Pareto Tail Modeling in the Case of Laeken Indicators. SMPS 2010: 17-24 - [c5]Peter Filzmoser:
Soft Methods in Robust Statistics. SMPS 2010: 273-280 - [c4]Karel Hron, Peter Filzmoser:
Elements of Robust Regression for Data with Absolute and Relative Information. SMPS 2010: 329-335
2000 – 2009
- 2009
- [j6]Peter Filzmoser, Karel Hron, Clemens Reimann, Robert G. Garrett:
Robust factor analysis for compositional data. Comput. Geosci. 35(9): 1854-1861 (2009) - 2008
- [j5]Peter Filzmoser, Ricardo A. Maronna, Mark Werner:
Outlier identification in high dimensions. Comput. Stat. Data Anal. 52(3): 1694-1711 (2008) - 2007
- [j4]N. M. Neykov, Peter Filzmoser, R. Dimova, P. N. Neytchev:
Robust fitting of mixtures using the trimmed likelihood estimator. Comput. Stat. Data Anal. 52(1): 299-308 (2007) - 2005
- [j3]João A. Branco, Christophe Croux, Peter Filzmoser, Maria Rosário de Oliveira:
Robust canonical correlations: A comparative study. Comput. Stat. 20(2): 203-229 (2005) - [j2]Peter Filzmoser, Robert G. Garrett, Clemens Reimann:
Multivariate outlier detection in exploration geochemistry. Comput. Geosci. 31(5): 579-587 (2005) - [c3]Sven Serneels, Christophe Croux, Peter Filzmoser, Pierre J. Van Espen:
The Partial Robust M-approach. GfKl 2005: 230-237 - [c2]Peter Filzmoser, Sven Serneels, Christophe Croux, Pierre J. Van Espen:
Robust Multivariate Methods: The Projection Pursuit Approach. GfKl 2005: 270-277 - 2003
- [j1]Christophe Croux, Peter Filzmoser, G. Pison, Peter J. Rousseeuw:
Fitting multiplicative models by robust alternating regressions. Stat. Comput. 13(1): 23-36 (2003)
1990 – 1999
- 1998
- [c1]Christophe Croux, Peter Filzmoser:
Robust Factorization of a Data Matrix. COMPSTAT 1998: 245-250
Coauthor Index
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last updated on 2024-10-07 21:18 CEST by the dblp team
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