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ORCIDDavid M. J. Tax
David Martinus Johannes Tax
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- affiliation: Delft University of Technology, The Netherlands
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2020 – today
- 2024
[j38]Ramin Ghorbani
, Marcel J. T. Reinders, David M. J. Tax:
Personalized anomaly detection in PPG data using representation learning and biometric identification. Biomed. Signal Process. Control. 94: 106216 (2024)- [j37]Aleksandr Dekhovich, David M. J. Tax, Marcel H. F. Sluiter, Miguel A. Bessa:
Neural network relief: a pruning algorithm based on neural activity. Mach. Learn. 113(5): 2597-2618 (2024) - [c75]Kim van den Houten, David M. J. Tax, Esteban Freydell, Mathijs de Weerdt:
Learning from Scenarios for Repairable Stochastic Scheduling. CPAIOR (2) 2024: 234-242 - [c74]Ramin Ghorbani, Marcel J. T. Reinders, David M. J. Tax:
PATE: Proximity-Aware Time Series Anomaly Evaluation. KDD 2024: 872-883 - [i29]Mahdi Naderibeni, Marcel J. T. Reinders, Liang Wu, David M. J. Tax:
Learning solutions of parametric Navier-Stokes with physics-informed neural networks. CoRR abs/2402.03153 (2024) - [i28]Ramin Ghorbani, Marcel J. T. Reinders, David M. J. Tax:
RESTAD: REconstruction and Similarity based Transformer for time series Anomaly Detection. CoRR abs/2405.07509 (2024) - [i27]Ramin Ghorbani, Marcel J. T. Reinders, David M. J. Tax:
PATE: Proximity-Aware Time series anomaly Evaluation. CoRR abs/2405.12096 (2024) - [i26]Kim van den Houten, Léon Planken, Esteban Freydell, David M. J. Tax, Mathijs de Weerdt:
Proactive and Reactive Constraint Programming for Stochastic Project Scheduling with Maximal Time-Lags. CoRR abs/2409.09107 (2024) - 2023
- [j36]Aleksandr Dekhovich, David M. J. Tax, Marcel H. F. Sluiter, Miguel A. Bessa:
Continual prune-and-select: class-incremental learning with specialized subnetworks. Appl. Intell. 53(14): 17849-17864 (2023) - [j35]Antonella Mensi, David M. J. Tax, Manuele Bicego:
Detecting outliers from pairwise proximities: Proximity isolation forests. Pattern Recognit. 138: 109334 (2023) - [c73]Yuko Kato, David M. J. Tax, Marco Loog:
A Review of Nonconformity Measures for Conformal Prediction in Regression. COPA 2023: 369-383 - [c72]Ramin Ghorbani, Marcel J. T. Reinders, David M. J. Tax:
Self-Supervised PPG Representation Learning Shows High Inter-Subject Variability. ICMLT 2023: 127-132 - [c71]Kim van den Houten, Mathijs de Weerdt, David M. J. Tax, Esteban Freydell, Eva Christoupoulou, Alessandro Nati:
Rolling-Horizon Simulation Optimization For A Multi-Objective Biomanufacturing Scheduling Problem. WSC 2023: 1912-1923 - [i25]Aleksandr Dekhovich, Marcel H. F. Sluiter, David M. J. Tax, Miguel A. Bessa:
iPINNs: Incremental learning for Physics-informed neural networks. CoRR abs/2304.04854 (2023) - [i24]Ramin Ghorbani, Marcel J. T. Reinders, David M. J. Tax:
Personalized Anomaly Detection in PPG Data using Representation Learning and Biometric Identification. CoRR abs/2307.06380 (2023) - [i23]Michael Beekhuizen, Arman Naseri, David M. J. Tax, Ivo van der Bilt, Marcel J. T. Reinders:
Improving performance of heart rate time series classification by grouping subjects. CoRR abs/2311.13285 (2023) - [i22]Kim van den Houten, David M. J. Tax, Esteban Freydell, Mathijs de Weerdt:
Learning From Scenarios for Stochastic Repairable Scheduling. CoRR abs/2312.03492 (2023) - 2022
- [j34]Morteza Moradi, Ramin Ghorbani, Stefano Sfarra, David M. J. Tax, Dimitrios Zarouchas:
A Spatiotemporal Deep Neural Network Useful for Defect Identification and Reconstruction of Artworks Using Infrared Thermography. Sensors 22(23): 9361 (2022) - [c70]Yuko Kato, David M. J. Tax, Marco Loog:
A View on Model Misspecification in Uncertainty Quantification. BNAIC/BENELEARN 2022: 65-77 - [c69]Stephanie Tan, David M. J. Tax, Hayley Hung:
Conversation Group Detection With Spatio-Temporal Context. ICMI 2022: 170-180 - [i21]Stephanie Tan, David M. J. Tax, Hayley Hung:
Conversation Group Detection With Spatio-Temporal Context. CoRR abs/2206.02559 (2022) - [i20]Aleksandr Dekhovich, David M. J. Tax, Marcel H. F. Sluiter, Miguel A. Bessa:
Continual Prune-and-Select: Class-incremental learning with specialized subnetworks. CoRR abs/2208.04952 (2022) - [i19]Yuko Kato, David M. J. Tax, Marco Loog:
A view on model misspecification in uncertainty quantification. CoRR abs/2210.16938 (2022) - [i18]Ramin Ghorbani, Marcel J. T. Reinders, David M. J. Tax:
Self-Supervised PPG Representation Learning Shows High Inter-Subject Variability. CoRR abs/2212.04902 (2022) - 2021
- [j33]Stephanie Tan, David M. J. Tax, Hayley Hung:
Multimodal Joint Head Orientation Estimation in Interacting Groups via Proxemics and Interaction Dynamics. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 5(1): 35:1-35:22 (2021) - [j32]Taygun Kekeç, David M. J. Tax:
Sem2Vec: Semantic Word Vectors with Bidirectional Constraint Propagations. IEEE Trans. Knowl. Data Eng. 33(4): 1750-1762 (2021) - [c68]Stephanie Tan, David M. J. Tax, Hayley Hung:
Head and Body Orientation Estimation with Sparse Weak Labels in Free Standing Conversational Settings. DYAD@ICCV 2021: 179-203 - [i17]Aleksandr Dekhovich, David M. J. Tax, Marcel H. F. Sluiter, Miguel A. Bessa:
Neural network relief: a pruning algorithm based on neural activity. CoRR abs/2109.10795 (2021) - 2020
- [j31]Wenjie Pei, Hamdi Dibeklioglu, Tadas Baltrusaitis, David M. J. Tax:
Attended End-to-End Architecture for Age Estimation From Facial Expression Videos. IEEE Trans. Image Process. 29: 1972-1984 (2020) - [j30]Laura Cabrera Quiros, David M. J. Tax, Hayley Hung:
Gestures In-The-Wild: Detecting Conversational Hand Gestures in Crowded Scenes Using a Multimodal Fusion of Bags of Video Trajectories and Body Worn Acceleration. IEEE Trans. Multim. 22(1): 138-147 (2020) - [c67]Antonella Mensi, Manuele Bicego, David M. J. Tax:
Proximity Isolation Forests. ICPR 2020: 8021-8028 - [c66]Antonella Mensi, Alessio Franzoni, David M. J. Tax, Manuele Bicego:
An Alternative Exploitation of Isolation Forests for Outlier Detection. S+SSPR 2020: 34-44 - [i16]Marco Loog, Tom J. Viering, Alexander Mey, Jesse H. Krijthe, David M. J. Tax:
A Brief Prehistory of Double Descent. CoRR abs/2004.04328 (2020)
2010 – 2019
- 2019
- [j29]Taygun Kekeç, David Mimno, David M. J. Tax:
Boosted negative sampling by quadratically constrained entropy maximization. Pattern Recognit. Lett. 125: 310-317 (2019) - [j28]Antonella Mensi, Manuele Bicego, Pietro Lovato, Marco Loog, David M. J. Tax:
A dissimilarity-based multiple instance learning approach for protein remote homology detection. Pattern Recognit. Lett. 128: 231-236 (2019) - [c65]Ajaya Adhikari, David M. J. Tax, Riccardo Satta, Matthias Faeth:
LEAFAGE: Example-based and Feature importance-based Explanations for Black-box ML models. FUZZ-IEEE 2019: 1-7 - 2018
- [j27]Wenjie Pei, Hamdi Dibeklioglu, David M. J. Tax, Laurens van der Maaten:
Multivariate Time-Series Classification Using the Hidden-Unit Logistic Model. IEEE Trans. Neural Networks Learn. Syst. 29(4): 920-931 (2018) - [c64]Taygun Kekeç, Laurens van der Maaten, David M. J. Tax:
PAWE: Polysemy Aware Word Embeddings. ICISDM 2018: 7-13 - [c63]Stephanie Tan, David M. J. Tax, Hayley Hung:
Improving Temporal Interpolation of Head and Body Pose using Gaussian Process Regression in a Matrix Completion Setting. GIFT@ICMI 2018: 3:1-3:8 - [c62]Antonella Mensi, Manuele Bicego, Pietro Lovato, Marco Loog, David M. J. Tax:
Protein Remote Homology Detection Using Dissimilarity-Based Multiple Instance Learning. S+SSPR 2018: 119-129 - [i15]Wenjie Pei, David M. J. Tax:
Unsupervised Learning of Sequence Representations by Autoencoders. CoRR abs/1804.00946 (2018) - [i14]Veronika Cheplygina, David M. J. Tax:
Characterizing multiple instance datasets. CoRR abs/1806.08186 (2018) - [i13]Ajaya Adhikari, David M. J. Tax, Riccardo Satta, Matthias Faeth:
Example and Feature importance-based Explanations for Black-box Machine Learning Models. CoRR abs/1812.09044 (2018) - 2017
- [c61]Wenjie Pei, Jie Yang, Zhu Sun, Jie Zhang, Alessandro Bozzon, David M. J. Tax:
Interacting Attention-gated Recurrent Networks for Recommendation. CIKM 2017: 1459-1468 - [c60]Wenjie Pei, Tadas Baltrusaitis, David M. J. Tax, Louis-Philippe Morency:
Temporal Attention-Gated Model for Robust Sequence Classification. CVPR 2017: 820-829 - [i12]Veronika Cheplygina, Lauge Sørensen, David M. J. Tax, Jesper Holst Pedersen, Marco Loog, Marleen de Bruijne:
Classification of COPD with Multiple Instance Learning. CoRR abs/1703.04980 (2017) - [i11]Veronika Cheplygina, Lauge Sørensen, David M. J. Tax, Marleen de Bruijne, Marco Loog:
Label Stability in Multiple Instance Learning. CoRR abs/1703.04986 (2017) - [i10]Wenjie Pei, Jie Yang, Zhu Sun, Jie Zhang, Alessandro Bozzon, David M. J. Tax:
Interacting Attention-gated Recurrent Networks for Recommendation. CoRR abs/1709.01532 (2017) - [i9]Wenjie Pei, Hamdi Dibeklioglu, Tadas Baltrusaitis, David M. J. Tax:
Attended End-to-end Architecture for Age Estimation from Facial Expression Videos. CoRR abs/1711.08690 (2017) - 2016
- [j26]André Eugênio Lazzaretti, David Martinus Johannes Tax, Hugo Vieira Neto, Vitor Hugo Ferreira:
Novelty detection and multi-class classification in power distribution voltage waveforms. Expert Syst. Appl. 45: 322-330 (2016) - [j25]Annetje C. P. Guédon, M. Paalvast, F. C. Meeuwsen, David M. J. Tax, A. P. van Dijke, L. S. G. L. Wauben, M. van der Elst, Jenny Dankelman, John van den Dobbelsteen:
'It is Time to Prepare the Next patient' Real-Time Prediction of Procedure Duration in Laparoscopic Cholecystectomies. J. Medical Syst. 40(12): 271:1-271:6 (2016) - [j24]Veronika Cheplygina, David M. J. Tax, Marco Loog:
Dissimilarity-Based Ensembles for Multiple Instance Learning. IEEE Trans. Neural Networks Learn. Syst. 27(6): 1379-1391 (2016) - [c59]Taygun Kekeç, David M. J. Tax:
Robust Gram Embeddings. EMNLP 2016: 1060-1065 - [c58]Dirk W. J. Meijer, David M. J. Tax:
Regularizing AdaBoost with validation sets of increasing size. ICPR 2016: 192-197 - [c57]David M. J. Tax, Feng Wang:
Class-dependent, non-convex losses to optimize precision. ICPR 2016: 3314-3319 - [c56]David M. J. Tax, Veronika Cheplygina, Robert P. W. Duin, Jan van de Poll:
The Similarity Between Dissimilarities. S+SSPR 2016: 84-94 - [i8]Feng Wang, David M. J. Tax:
Survey on the attention based RNN model and its applications in computer vision. CoRR abs/1601.06823 (2016) - [i7]Wenjie Pei, David M. J. Tax, Laurens van der Maaten:
Modeling Time Series Similarity with Siamese Recurrent Networks. CoRR abs/1603.04713 (2016) - [i6]Wenjie Pei, Tadas Baltrusaitis, David M. J. Tax, Louis-Philippe Morency:
Temporal Attention-Gated Model for Robust Sequence Classification. CoRR abs/1612.00385 (2016) - 2015
- [j23]Veronika Cheplygina, David M. J. Tax, Marco Loog:
Multiple instance learning with bag dissimilarities. Pattern Recognit. 48(1): 264-275 (2015) - [j22]Ethem Alpaydin, Veronika Cheplygina, Marco Loog, David M. J. Tax:
Single- vs. multiple-instance classification. Pattern Recognit. 48(9): 2831-2838 (2015) - [j21]Veronika Cheplygina, David M. J. Tax, Marco Loog:
On classification with bags, groups and sets. Pattern Recognit. Lett. 59: 11-17 (2015) - [c55]A. C. P. Guédon, M. Paalvast, F. C. Meeuwsen, David M. J. Tax, A. P. van Dijke, L. S. G. L. Wauben, M. van der Elst, Jenny Dankelman, John van den Dobbelsteen:
Real-time estimation of surgical procedure duration. HealthCom 2015: 6-10 - [c54]Veronika Cheplygina, Lauge Sørensen, David M. J. Tax, Marleen de Bruijne, Marco Loog:
Label Stability in Multiple Instance Learning. MICCAI (1) 2015: 539-546 - [c53]Veronika Cheplygina, David M. J. Tax:
Characterizing Multiple Instance Datasets. SIMBAD 2015: 15-27 - [c52]André Eugênio Lazzaretti, David M. J. Tax:
An Adaptive Radial Basis Function Kernel for Support Vector Data Description. SIMBAD 2015: 103-116 - [i5]Wenjie Pei, Hamdi Dibeklioglu, David M. J. Tax, Laurens van der Maaten:
Time Series Classification using the Hidden-Unit Logistic Model. CoRR abs/1506.05085 (2015) - 2014
- [c51]Veronika Cheplygina, Lauge Sørensen, David M. J. Tax, Jesper Johannes Holst Pedersen, Marco Loog, Marleen de Bruijne:
Classification of COPD with Multiple Instance Learning. ICPR 2014: 1508-1513 - [c50]David M. J. Tax, Herman M. J. Sontrop, Marcel J. T. Reinders, Perry D. Moerland:
The Effect of Aggregating Subtype Performances Depends Strongly on the Performance Measure Used. ICPR 2014: 3720-3725 - [c49]Veronika Cheplygina, David M. J. Tax, Marco Loog, Aasa Feragen:
Network-Guided Group Feature Selection for Classification of Autism Spectrum Disorder. MLMI 2014: 190-197 - [c48]Siamak Hajizadeh, Zili Li, Rolf P. B. J. Dollevoet, David M. J. Tax:
Evaluating Classification Performance with only Positive and Unlabeled Samples. S+SSPR 2014: 233-242 - [i4]Veronika Cheplygina, David M. J. Tax, Marco Loog:
Dissimilarity-based Ensembles for Multiple Instance Learning. CoRR abs/1402.1349 (2014) - [i3]David M. J. Tax, Veronika Cheplygina, Marco Loog:
Quantile Representation for Indirect Immunofluorescence Image Classification. CoRR abs/1402.1371 (2014) - [i2]Veronika Cheplygina, David M. J. Tax, Marco Loog:
On Classification with Bags, Groups and Sets. CoRR abs/1406.0281 (2014) - 2013
- [j20]Yan Li, David M. J. Tax, Robert P. W. Duin, Marco Loog:
Multiple-instance learning as a classifier combining problem. Pattern Recognit. 46(3): 865-874 (2013) - [c47]Floris Gaisser, Maja Rudinac, Pieter P. Jonker, David M. J. Tax:
Online face recognition and learning for cognitive robots. ICAR 2013: 1-9 - [c46]Veronika Cheplygina, David M. J. Tax, Marco Loog:
Combining Instance Information to Classify Bags. MCS 2013: 13-24 - [c45]Yan Li, David M. J. Tax, Robert P. W. Duin, Marco Loog:
The Link between Multiple-Instance Learning and Learning from Only Positive and Unlabelled Examples. MCS 2013: 157-166 - [c44]Yenisel Plasencia Calana, Veronika Cheplygina, Robert P. W. Duin, Edel B. García Reyes, Mauricio Orozco-Alzate, David M. J. Tax, Marco Loog:
On the Informativeness of Asymmetric Dissimilarities. SIMBAD 2013: 75-89 - [i1]Veronika Cheplygina, David M. J. Tax, Marco Loog:
Multiple Instance Learning with Bag Dissimilarities. CoRR abs/1309.5643 (2013) - 2012
- [j19]Wan-Jui Lee, Veronika Cheplygina, David M. J. Tax, Marco Loog, Robert P. W. Duin:
Bridging Structure and Feature Representations in Graph Matching. Int. J. Pattern Recognit. Artif. Intell. 26(5) (2012) - [j18]Yan Li, David M. J. Tax, Marco Loog:
Scale selection for supervised image segmentation. Image Vis. Comput. 30(12): 991-1003 (2012) - [c43]Swaminathan Sankaranarayanan, François Brémond, David M. J. Tax:
Qualitative Evaluation of Detection and Tracking Performance. AVSS 2012: 362-367 - [c42]Peng Xu, David M. J. Tax, Alan Hanjalic:
A structure-based video representation for web video categorization. ICPR 2012: 433-436 - [c41]Veronika Cheplygina, David M. J. Tax, Marco Loog:
Does one rotten apple spoil the whole barrel? ICPR 2012: 1156-1159 - [c40]Veronika Cheplygina, David M. J. Tax, Marco Loog:
Class-Dependent Dissimilarity Measures for Multiple Instance Learning. SSPR/SPR 2012: 602-610 - 2011
- [c39]Veronika Cheplygina, David M. J. Tax:
Pruned Random Subspace Method for One-Class Classifiers. MCS 2011: 96-105 - [c38]Peng Xu, David M. J. Tax, Alan Hanjalic:
TUD-MM at MediaEval 2011 Genre Tagging Task: Video search reranking for genre tagging. MediaEval 2011 - [c37]Yan Li, David M. J. Tax, Marco Loog:
Supervised Scale-Invariant Segmentation (and Detection). SSVM 2011: 350-361 - [c36]David M. J. Tax, Marco Loog, Robert P. W. Duin, Veronika Cheplygina, Wan-Jui Lee:
Bag Dissimilarities for Multiple Instance Learning. SIMBAD 2011: 222-234 - [c35]Babak Loni, Gijs van Tulder, Pascal Wiggers, David M. J. Tax, Marco Loog:
Question Classification by Weighted Combination of Lexical, Syntactic and Semantic Features. TSD 2011: 243-250 - 2010
- [c34]Robert P. W. Duin, Marco Loog, Elzbieta Pekalska, David M. J. Tax:
Feature-Based Dissimilarity Space Classification. ICPR Contests 2010: 46-55 - [c33]David M. J. Tax, E. Hendriks, Michel François Valstar, Maja Pantic:
The Detection of Concept Frames Using Clustering Multi-instance Learning. ICPR 2010: 2917-2920 - [c32]Lauge Sørensen, Marco Loog, David M. J. Tax, Wan-Jui Lee, Marleen de Bruijne, Robert P. W. Duin:
Dissimilarity-Based Multiple Instance Learning. SSPR/SPR 2010: 129-138
2000 – 2009
- 2009
- [j17]Piotr Juszczak, David M. J. Tax, Elzbieta Pekalska, Robert P. W. Duin:
Minimum spanning tree based one-class classifier. Neurocomputing 72(7-9): 1859-1869 (2009) - [j16]Yulia Arzhaeva, David M. J. Tax, Bram van Ginneken:
Dissimilarity-based classification in the absence of local ground truth: Application to the diagnostic interpretation of chest radiographs. Pattern Recognit. 42(9): 1768-1776 (2009) - [j15]Manuele Bicego, Elzbieta Pekalska, David M. J. Tax, Robert P. W. Duin:
Component-based discriminative classification for hidden Markov models. Pattern Recognit. 42(11): 2637-2648 (2009) - [c31]David M. J. Tax, Marco Loog, Robert P. W. Duin:
Optimal Mean-Precision Classifier. MCS 2009: 72-81 - [c30]Marco Loog, Yan Li, David M. J. Tax:
Maximum Membership Scale Selection. MCS 2009: 468-477 - 2008
- [j14]Sergio Escalera, David M. J. Tax, Oriol Pujol, Petia Radeva, Robert P. W. Duin:
Subclass Problem-Dependent Design for Error-Correcting Output Codes. IEEE Trans. Pattern Anal. Mach. Intell. 30(6): 1041-1054 (2008) - [j13]David M. J. Tax, Robert P. W. Duin:
Growing a multi-class classifier with a reject option. Pattern Recognit. Lett. 29(10): 1565-1570 (2008) - [c29]Paolo Simeone, David M. J. Tax, Robert P. W. Duin, Francesco Tortorella:
A Fast Approach to Improve Classification Performance of ECOC Classification Systems. SSPR/SPR 2008: 459-468 - [c28]David M. J. Tax, Robert P. W. Duin:
Learning Curves for the Analysis of Multiple Instance Classifiers. SSPR/SPR 2008: 724-733 - 2006
- [j12]Stefan Harmeling, Guido Dornhege, David M. J. Tax, Frank C. Meinecke, Klaus-Robert Müller:
From outliers to prototypes: Ordering data. Neurocomputing 69(13-15): 1608-1618 (2006) - [j11]Thomas C. W. Landgrebe, David M. J. Tax, Pavel Paclík, Robert P. W. Duin:
The interaction between classification and reject performance for distance-based reject-option classifiers. Pattern Recognit. Lett. 27(8): 908-917 (2006) - [c27]David M. J. Tax, Robert P. W. Duin:
Linear model combining by optimizing the Area under the ROC curve. ICPR (4) 2006: 119-122 - [c26]Yulia Arzhaeva, Bram van Ginneken, David M. J. Tax:
Image Classification from Generalized Image Distance Features: Application to Detection of Interstitial Disease in Chest Radiographs. ICPR (1) 2006: 367-370 - [c25]Piotr Juszczak, David M. J. Tax, Serguei Verzakov, Robert P. W. Duin:
Domain Based LDA and QDA. ICPR (2) 2006: 788-791 - [c24]Yulia Arzhaeva, David M. J. Tax, Bram van Ginneken:
Improving computer-aided diagnosis of interstitial disease in chest radiographs by combining one-class and two-class classifiers. Medical Imaging: Image Processing 2006: 614458 - [c23]David M. J. Tax, Piotr Juszczak, Elzbieta Pekalska, Robert P. W. Duin:
Outlier Detection Using Ball Descriptions with Adjustable Metric. SSPR/SPR 2006: 587-595 - 2005
- [j10]Cor J. Veenman, David M. J. Tax:
LESS: A Model-Based Classifier for Sparse Subspaces. IEEE Trans. Pattern Anal. Mach. Intell. 27(9): 1496-1500 (2005) - [c22]David M. J. Tax, Cor J. Veenman:
Turning the hyperparameter of an AUC-optimized classifier. BNAIC 2005: 224-231 - [c21]Cor J. Veenman, David M. J. Tax:
A Weighted Nearest Mean Classifier for Sparse Subspaces. CVPR (2) 2005: 1171-1176 - [c20]Pavel Paclík, Thomas C. W. Landgrebe, David M. J. Tax, Robert P. W. Duin:
On Deriving the Second-Stage Training Set for Trainable Combiners. Multiple Classifier Systems 2005: 136-146 - [c19]Thomas C. W. Landgrebe, Pavel Paclík, David M. J. Tax, Robert P. W. Duin:
Optimising Two-Stage Recognition Systems. Multiple Classifier Systems 2005: 206-215 - 2004
- [j9]Carmen Lai, David M. J. Tax, Robert P. W. Duin, Elzbieta Pekalska, Pavel Paclík:
A Study On Combining Image Representations For Image Classification And Retrieval. Int. J. Pattern Recognit. Artif. Intell. 18(5): 867-890 (2004) - [j8]David M. J. Tax, Robert P. W. Duin:
Support Vector Data Description. Mach. Learn. 54(1): 45-66 (2004) - [c18]QingHua Wang, Luís Seabra Lopes, David M. J. Tax:
Visual Object Recognition Through One-Class Learning. ICIAR (1) 2004: 463-470 - [c17]Robert P. W. Duin, Elzbieta Pekalska, David M. J. Tax:
The Characterization of Classification Problems by Classifier Disagreements. ICPR (1) 2004: 140-143 - [c16]David M. J. Tax, Klaus-Robert Müller:
A Consistency-Based Model Selection for One-Class Classification. ICPR (3) 2004: 363-366 - [c15]Thomas C. W. Landgrebe, Pavel Paclík, David M. J. Tax, Serguei Verzakov, Robert P. W. Duin:
Cost-Based Classifier Evaluation for Imbalanced Problems. SSPR/SPR 2004: 762-770 - 2003
- [j7]David M. J. Tax, Piotr Juszczak:
Kernel Whitening for One-Class Classification. Int. J. Pattern Recognit. Artif. Intell. 17(3): 333-347 (2003) - [c14]David M. J. Tax, Klaus-Robert Müller:
Feature Extraction for One-Class Classification. ICANN 2003: 342-349 - [c13]David M. J. Tax, Pavel Laskov:
Online SVM learning: from classification to data description and back. NNSP 2003: 499-508 - 2002
- [c12]David M. J. Tax, Robert P. W. Duin:
Using Two-Class Classifiers for Multiclass Classification. ICPR (2) 2002: 124-127 - [c11]Carmen Lai, David M. J. Tax, Robert P. W. Duin, Elzbieta Pekalska, Pavel Paclík:
On Combining One-Class Classifiers for Image Database Retrieval. Multiple Classifier Systems 2002: 212-221 - [c10]Elzbieta Pekalska, David M. J. Tax, Robert P. W. Duin:
One-Class LP Classifiers for Dissimilarity Representations. NIPS 2002: 761-768 - [c9]David M. J. Tax, Piotr Juszczak:
Kernel Whitening for One-Class Classification. SVM 2002: 40-52 - 2001
- [j6]David M. J. Tax, Robert P. W. Duin:
Uniform Object Generation for Optimizing One-class Classifiers. J. Mach. Learn. Res. 2: 155-173 (2001) - [c8]David M. J. Tax, Robert P. W. Duin:
Combining One-Class Classifiers. Multiple Classifier Systems 2001: 299-308 - 2000
- [j5]David M. J. Tax, Martijn van Breukelen, Robert P. W. Duin, Josef Kittler:
Combining multiple classifiers by averaging or by multiplying? Pattern Recognit. 33(9): 1475-1485 (2000) - [c7]David M. J. Tax, Robert P. W. Duin:
Data Description in Subspaces. ICPR 2000: 2672-2675 - [c6]Robert P. W. Duin, David M. J. Tax:
Experiments with Classifier Combining Rules. Multiple Classifier Systems 2000: 16-29
1990 – 1999
- 1999
- [j4]David M. J. Tax, Robert P. W. Duin:
Support vector domain description. Pattern Recognit. Lett. 20(11-13): 1191-1199 (1999) - [c5]David M. J. Tax, Robert P. W. Duin:
Data domain description using support vectors. ESANN 1999: 251-256 - [c4]David M. J. Tax, Alexander Ypma, Robert P. W. Duin:
Pump Failure Detection Using Support Vector Data Descriptions. IDA 1999: 415-426 - 1998
- [j3]Martijn van Breukelen, Robert P. W. Duin, David M. J. Tax, J. E. den Hartog:
Handwritten digit recognition by combined classifiers. Kybernetika 34(4): 381-386 (1998) - [j2]Robert P. W. Duin, Dick de Ridder, David M. J. Tax:
Featureless pattern classification. Kybernetika 34(4): 399-404 (1998) - [c3]David M. J. Tax, Robert P. W. Duin:
Outlier Detection Using Classifier Instability. SSPR/SPR 1998: 593-601 - [c2]Robert P. W. Duin, David M. J. Tax:
Classifier Conditional Posterior Probabilities. SSPR/SPR 1998: 611-619 - 1997
- [j1]Robert P. W. Duin, Dick de Ridder, David M. J. Tax:
Experiments with a featureless approach to pattern recognition. Pattern Recognit. Lett. 18(11-13): 1159-1166 (1997) - 1996
- [c1]David M. J. Tax, Hilbert J. Kappen:
Learning Structure with Many-Take-All Networks. ICANN 1996: 95-100
Coauthor Index
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