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2020 – today
- 2024
[j7]Di Wu
, Renchi Zhang, Ameya Pore, Diego Dall'Alba, Xuan Thao Ha, Zhen Li, Yao Zhang, Fernando Herrera, Mouloud Ourak, Wojtek Kowalczyk, Elena De Momi, Alícia Casals, Jenny Dankelman, Jens Kober, Arianna Menciassi, Paolo Fiorini, Emmanuel B. Vander Poorten:
A review on machine learning in flexible surgical and interventional robots: Where we are and where we are going. Biomed. Signal Process. Control. 93: 106179 (2024)- 2023
- [c34]Hadar Shavit, Filip Jatelnicki, Pol Mor-Puigventós, Wojtek Kowalczyk:
From Xception to NEXcepTion: New Design Decisions and Neural Architecture Search. ICPRAM 2023: 229-236 - 2022
- [i2]Hadar Shavit, Filip Jatelnicki, Pol Mor-Puigventós, Wojtek Kowalczyk:
From Xception to NEXcepTion: New Design Decisions and Neural Architecture Search. CoRR abs/2212.08448 (2022) - 2020
- [j6]Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael Emmerich, Thomas Bäck:
Cluster-based Kriging approximation algorithms for complexity reduction. Appl. Intell. 50(3): 778-791 (2020) - [j5]Wouter B. Verschoof-van der Vaart, Karsten Lambers, Wojtek Kowalczyk, Quentin P. J. Bourgeois:
Combining Deep Learning and Location-Based Ranking for Large-Scale Archaeological Prospection of LiDAR Data from The Netherlands. ISPRS Int. J. Geo Inf. 9(5): 293 (2020) - [c33]Jichen Wu, Maarten H. Lamers, Wojtek Kowalczyk:
Being Creative: A Cross-Domain Mapping Network. ICCC 2020: 220-227 - [c32]Jiawen Kong, Thiago Rios, Wojtek Kowalczyk, Stefan Menzel, Thomas Bäck:
On the Performance of Oversampling Techniques for Class Imbalance Problems. PAKDD (2) 2020: 84-96 - [c31]Jiawen Kong, Wojtek Kowalczyk, Stefan Menzel, Thomas Bäck:
Improving Imbalanced Classification by Anomaly Detection. PPSN (1) 2020: 512-523 - [d2]Jiawen Kong, Wojtek Kowalczyk, Duc Anh Nguyen, Stefan Menzel, Thomas Bäck:
Hyperparameter Optimisation for Improving Classification under Class Imbalance. Zenodo, 2020
- [d1]Jiawen Kong, Thiago Rios, Wojtek Kowalczyk, Stefan Menzel, Thomas Bäck:
On the Performance of Oversampling Techniques for Class Imbalance Problems. Zenodo, 2020
2010 – 2019
- 2019
- [c30]Mark Pijnenburg, Wojtek Kowalczyk:
Are Similar Cases Treated Similarly? A Comparison Between Process Workers. BIS (2) 2019: 162-176 - [c29]Mark Pijnenburg, Wojtek Kowalczyk:
Extending an Anomaly Detection Benchmark with Auto-encoders, Isolation Forests, and RBMs. ICIST 2019: 498-515 - [c28]Jiawen Kong, Wojtek Kowalczyk, Duc Anh Nguyen, Thomas Bäck, Stefan Menzel:
Hyperparameter Optimisation for Improving Classification under Class Imbalance. SSCI 2019: 3072-3078 - 2018
- [c27]Bas van Stein, Hao Wang, Wojtek Kowalczyk, Thomas Bäck:
A Novel Uncertainty Quantification Method for Efficient Global Optimization. IPMU (3) 2018: 480-491 - [c26]Mark Pijnenburg, Wojtek Kowalczyk:
Singular Outliers: Finding Common Observations with an Uncommon Feature. IPMU (3) 2018: 492-503 - 2017
- [j4]Eelke B. Lenselink, Niels ten Dijke, Brandon J. Bongers, George Papadatos, Herman W. T. van Vlijmen, Wojtek Kowalczyk, Adriaan P. IJzerman, Gerard J. P. van Westen:
Beyond the hype: deep neural networks outperform established methods using a ChEMBL bioactivity benchmark set. J. Cheminformatics 9(1): 45 (2017) - [c25]Mark Pijnenburg, Wojtek Kowalczyk:
Extending Logistic Regression Models with Factorization Machines. ISMIS 2017: 323-332 - [i1]Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael T. M. Emmerich, Thomas Bäck:
Cluster-based Kriging Approximation Algorithms for Complexity Reduction. CoRR abs/1702.01313 (2017) - 2016
- [c24]Bas van Stein, Hao Wang, Wojtek Kowalczyk, Michael T. M. Emmerich, Thomas Bäck:
Fuzzy clustering for Optimally Weighted Cluster Kriging. FUZZ-IEEE 2016: 939-945 - [c23]Bas van Stein, Wojtek Kowalczyk:
An Incremental Algorithm for Repairing Training Sets with Missing Values. IPMU (2) 2016: 175-186 - [c22]Bas van Stein, Wojtek Kowalczyk, Thomas Bäck:
Analysis and Visualization of Missing Value Patterns. IPMU (2) 2016: 187-198 - 2015
- [c21]Bas van Stein, Hao Wang, Wojtek Kowalczyk, Thomas Bäck, Michael Emmerich:
Optimally Weighted Cluster Kriging for Big Data Regression. IDA 2015: 310-321 - 2013
- [j3]C. Natalie van der Wal, Wojtek Kowalczyk:
Detecting changing emotions in human speech by machine and humans. Appl. Intell. 39(4): 675-691 (2013) - [c20]Martine Coene, Annemiek Hammer, Wojtek Kowalczyk, Louis ten Bosch, Bart Vaerenberg, Paul Govaerts:
Quantifying cross-linguistic variation in grapheme-to-phoneme mapping. INTERSPEECH 2013: 1854-1857 - [c19]Bart Vaerenberg, Louis ten Bosch, Wojtek Kowalczyk, Martine Coene, Herwig De Smet, Paul J. Govaerts:
Language-universal speech audiometry with automated scoring. INTERSPEECH 2013: 3608-3612 - [c18]Annemiek Hammer, Bart Vaerenberg, Wojtek Kowalczyk, Louis ten Bosch, Martine Coene, Paul J. Govaerts:
Balancing word lists in speech audiometry through large spoken language corpora. INTERSPEECH 2013: 3613-3616 - [c17]Rob M. Konijn, Wouter Duivesteijn, Wojtek Kowalczyk, Arno J. Knobbe:
Discovering Local Subgroups, with an Application to Fraud Detection. PAKDD (1) 2013: 1-12 - 2012
- [c16]Rob M. Konijn, Wojtek Kowalczyk:
Hunting for Fraudsters in Random Forests. HAIS (1) 2012: 174-185 - [c15]Wojtek Kowalczyk, C. Natalie van der Wal:
Detecting Changing Emotions in Natural Speech. IEA/AIE 2012: 491-500 - 2011
- [j2]David Samoocha, Ingrid A. K. Snels, David J. Bruinvels, Johannes R. Anema, Wojtek Kowalczyk, Allard J. van der Beek:
Process evaluation of a web-based intervention aimed at empowerment of disability benefit claimants. BMC Medical Informatics Decis. Mak. 11: 10 (2011) - [c14]Wojtek Kowalczyk, Zoltán Szlávik, Martijn C. Schut:
The Impact of Recommender Systems on Item-, User-, and Rating-Diversity. ADMI 2011: 261-287 - [c13]Rob M. Konijn, Wojtek Kowalczyk:
Finding Fraud in Health Insurance Data with Two-Layer Outlier Detection Approach. DaWaK 2011: 394-405 - [c12]Zoltán Szlávik, Wojtek Kowalczyk, Martijn C. Schut:
Diversity Measurement of Recommender Systems under Different User Choice Models. ICWSM 2011 - 2010
- [c11]Rob M. Konijn, Wojtek Kowalczyk:
An Interactive Approach to Outlier Detection. RSKT 2010: 379-385
2000 – 2009
- 2006
- [c10]A. E. Eiben, Mark Horvath, Wojtek Kowalczyk, Martijn C. Schut:
Reinforcement Learning for Online Control of Evolutionary Algorithms. ESOA 2006: 151-160 - [c9]Jan Peter Patist, Wojtek Kowalczyk, Elena Marchiori:
Maintaining Gaussian Mixture Models of Data Streams Under Block Evolution. International Conference on Computational Science (1) 2006: 1071-1074 - 2005
- [c8]Nikos Vlassis, Yiannis Sfakianakis, Wojtek Kowalczyk:
Gossip-Based Greedy Gaussian Mixture Learning. Panhellenic Conference on Informatics 2005: 349-359 - [c7]Krisztian Balog, Peter Hofgesang, Wojtek Kowalczyk:
Modeling Navigation Patterns of Visitors of Unstructured Websites. SGAI Conf. 2005: 116-129 - 2004
- [c6]Wojtek Kowalczyk, Nikos Vlassis:
Newscast EM. NIPS 2004: 713-720 - [c5]Márk Jelasity, Wojtek Kowalczyk, Maarten van Steen:
An Approach to Massively Distributed Aggregate Computing on Peer-to-Peer Networks. PDP 2004: 200-207 - 2003
- [c4]Wojtek Kowalczyk:
An Approximate Algorithm for Reverse Engineering of Multi-layer Perceptrons. SGAI Conf. 2003: 55-66
1990 – 1999
- 1998
- [j1]Frederik Jan Jüngen, Wojtek Kowalczyk:
Approximate algorithms for generalized maximum utility problems. J. Exp. Theor. Artif. Intell. 10(1): 49-62 (1998) - [c3]Wojtek Kowalczyk, Zdzislaw Piasta:
Rough-Set Inspired Approach to Knowledge Discovery in Business Databases. PAKDD 1998: 186-197 - 1996
- [c2]Frederik Jan Jüngen, Wojtek Kowalczyk:
Appriximate Algorithms for Maximum Utility Problems. CP 1996: 547-548 - [c1]Wojtek Kowalczyk:
An algorithm for training multilayer networks on non-numerical data. ESANN 1996
Coauthor Index
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last updated on 2024-10-22 20:13 CEST by the dblp team
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