Kurt Hornik

Walter Böhm, Kurt Hornik: A Kolmogorov-Smirnov Test for r Samples. Fundam. Inform. 117(1-4): 103-125 (2012)

Michael Hahsler, Sudheer Chelluboina, Kurt Hornik, Christian Buchta: The arules R-Package Ecosystem: Analyzing Interesting Patterns from Large Transaction Data Sets. Journal of Machine Learning Research 12: 2021-2025 (2011)

Norbert Walchhofer, Karl Anton Froeschl, Kurt Hornik: Adaptive Change Estimation in the Context of Online Market Monitoring. EUROCAST (1) 2011: 200-207

Wilhelm M. Geiger, Johannes Rauch, Patrick Mair, Kurt Hornik: Text Categorization in R: A Reduced N-Gram Approach. GfKl 2010: 341-349

Achim Zeileis, Kurt Hornik, Paul Murrell: Escaping RGBland: Selecting colors for statistical graphics. Computational Statistics & Data Analysis 53(9): 3259-3270 (2009)

Alexandros Karatzoglou, Ingo Feinerer, Kurt Hornik: Nonparametric Distribution Analysis for Text Mining. GfKl 2008: 295-305

Michael Hahsler, Christian Buchta, Kurt Hornik: Selective association rule generation. CoRR abs/0803.0954 (2008)

Michael Hahsler, Kurt Hornik: New probabilistic interest measures for association rules. CoRR abs/0803.0966 (2008)

Michael Hahsler, Kurt Hornik: New probabilistic interest measures for association rules. Intell. Data Anal. 11(5): 437-455 (2007)

Kurt Hornik, Walter Böhm: Hard and Soft Euclidean Consensus Partitions. GfKl 2007: 147-154

Michael Schauerhuber, Achim Zeileis, David Meyer, Kurt Hornik: Benchmarking Open-Source Tree Learners in R/RWeka. GfKl 2007: 389-396

Ingo Feinerer, Kurt Hornik: Text Mining of Supreme Administrative Court Jurisdictions. GfKl 2007: 569-576

Kurt Hornik, David Meyer: Deriving Consensus Rankings from Benchmarking Experiments. GfKl 2006: 163-170

Michael Hahsler, Kurt Hornik: Building on the Arules Infrastructure for Analyzing Transaction Data with R. GfKl 2006: 449-456

Michael Hahsler, Kurt Hornik, Thomas Reutterer: Implications of Probabilistic Data Modeling for Mining Association Rules. GfKl 2005: 598-605

Evgenia Dimitriadou, Markus Barth, Christian Windischberger, Kurt Hornik, Ewald Moser: A quantitative comparison of functional MRI cluster analysis. Artificial Intelligence in Medicine 31(1): 57-71 (2004)

Kurt Hornik: Cluster Ensembles. GfKl 2004: 65-72

Achim Zeileis, Christian Kleiber, Walter Krämer, Kurt Hornik: Testing and dating of structural changes in practice. Computational Statistics & Data Analysis 44(1-2): 109-123 (2003)

Andreas Weingessel, Kurt Hornik: A Robust Subspace Algorithm for Principal Component Analysis. Int. J. Neural Syst. 13(5): 307-313 (2003)

David Meyer, Friedrich Leisch, Kurt Hornik: The support vector machine under test. Neurocomputing 55(1-2): 169-186 (2003)

Evgenia Dimitriadou, Andreas Weingessel, Kurt Hornik: A Cluster Ensembles Framework. HIS 2003: 528-534

Evgenia Dimitriadou, Andreas Weingessel, Kurt Hornik: A Combination Scheme for Fuzzy Clustering. IJPRAI 16(7): 901-912 (2002)

Evgenia Dimitriadou, Andreas Weingessel, Kurt Hornik: A Combination Scheme for Fuzzy Clustering. AFSS 2002: 332-338

Evgenia Dimitriadou, Andreas Weingessel, Kurt Hornik: A Mixed Ensemble Approach for the Semi-supervised Problem. ICANN 2002: 571-576

Evgenia Dimitriadou, Andreas Weingessel, Kurt Hornik: Voting-Merging: An Ensemble Method for Clustering. ICANN 2001: 217-224

Georg Dorffner, Horst Bischof, Kurt Hornik (Eds.): Artificial Neural Networks - ICANN 2001, International Conference Vienna, Austria, August 21-25, 2001 Proceedings. Lecture Notes in Computer Science 2130, Springer 2001, isbn 3-540-42486-5

Adrian Trapletti, Friedrich Leisch, Kurt Hornik: Stationary and Integrated Autoregressive Neural Network Processes. Neural Computation 12(10): 2427-2450 (2000)

Andreas Weingessel, Kurt Hornik: Local PCA algorithms. IEEE Trans. Neural Netw. Learning Syst. 11(6): 1242-1250 (2000)

Konstantinos I. Diamantaras, Kurt Hornik, Michael G. Strintzis: Optimal linear compression under unreliable representation and robust PCA neural models. IEEE Transactions on Neural Networks 10(5): 1186-1195 (1999)

Friedrich Leisch, Lakhmi C. Jain, Kurt Hornik: Cross-validation with active pattern selection for neural-network classifiers. IEEE Transactions on Neural Networks 9(1): 35-41 (1998)

Friedrich Leisch, Adrian Trapletti, Kurt Hornik: Stationarity and Stability of Autoregressive Neural Network Processes. NIPS 1998: 267-273

Andreas Weingessel, Kurt Hornik: SVD Algorithms: APEX-like versus Subspace Methods. Neural Processing Letters 5(3): 177-184 (1997)

Andreas Weingessel, Horst Bischof, Kurt Hornik, Friedrich Leisch: Adaptive combination of PCA and VQ networks. IEEE Trans. Neural Netw. Learning Syst. 8(5): 1208-1211 (1997)

Kurt Hornik: Guest Editorial How to Submit Letters. IEEE Trans. Neural Netw. Learning Syst. 7(5): 1061 (1996)

Friedrich Leisch, Kurt Hornik: ARC-LH: A New Adaptive Resampling Algorithm for Improving ANN Classifiers. NIPS 1996: 522-528

Pierre Baldi, Kurt Hornik: Learning in linear neural networks: a survey. IEEE Trans. Neural Netw. Learning Syst. 6(4): 837-858 (1995)

Friedrich Leisch, Kurt Hornik, Lakhmi C. Jain: NN Classifiers: Reducing the Computational Cost of Cross-Validation by Active Pattern Selection. ANNES 1995: 91-94

Pierre Baldi, Kurt Hornik: Universal Approximnation and Learning of Trajectories Using Oscillators. NIPS 1995: 451-457

Chung-Ming Kuan, Kurt Hornik, Halbert White: A Convergence Result for Learning in Recurrent Neural Networks. Neural Computation 6(3): 420-440 (1994)

Kurt Hornik, Maxwell B. Stinchcombe, Halbert White, Peter Auer: Degree of Approximation Results for Feedforward Networks Approximating Unknown Mappings and Their Derivatives. Neural Computation 6(6): 1262-1275 (1994)

Horst Bischof, Kurt Hornik: PCA-Pyramids for Image Compression. NIPS 1994: 941-948

Kurt Hornik, Maxwell B. Stinchcombe, Halbert White: Letters to the editor. Neural Networks 6(1): 3 (1993)

Kurt Hornik, Chung-Ming Kuan: Convergence analysis of local feature extraction algorithms. Neural Networks 5(2): 229-240 (1992)

Kurt Hornik: Approximation capabilities of multilayer feedforward networks. Neural Networks 4(2): 251-257 (1991)

Kurt Hornik, Maxwell B. Stinchcombe, Halbert White: Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networks. Neural Networks 3(5): 551-560 (1990)

Pierre Baldi, Kurt Hornik: Neural networks and principal component analysis: Learning from examples without local minima. Neural Networks 2(1): 53-58 (1989)

Kurt Hornik, Maxwell B. Stinchcombe, Halbert White: Multilayer feedforward networks are universal approximators. Neural Networks 2(5): 359-366 (1989)