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2020 – today

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2020
[j6]
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Olga Fink, Qin Wang, Markus Svensén, Pierre Dersin, Wan-Jui Lee, Melanie Ducoffe:
Potential, challenges and future directions for deep learning in prognostics and health management applications. Eng. Appl. Artif. Intell. 92: 103678 (2020)
[c28]
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Wan-Jui Lee, Helia Jamshidi, Diederik M. Roijers:
Deep Reinforcement Learning for Solving Train Unit Shunting Problem with Interval Timing. EDCC Workshops 2020: 99-110

2010 – 2019

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2019
[c27]
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Paulo Roberto de Oliveira da Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay, Wan-Jui Lee, Uzay Kaymak:
Data-Driven Policy on Feasibility Determination for the Train Shunting Problem. BNAIC/BENELEARN 2019
[c26]
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Arno van de Ven, Yingqian Zhang, Wan-Jui Lee:
Boosting Local Search Using Machine Learning: A Study on Improving Local Search by Graph Classification in Determining Capacity of Shunting Yards. ICAART (Revised Selected Papers) 2019: 183-203
[c25]
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Arno van de Ven, Yingqian Zhang, Wan-Jui Lee, Rik Eshuis, Anna Wilbik:
Determining Capacity of Shunting Yards by Combining Graph Classification with Local Search. ICAART (2) 2019: 285-293
[c24]
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Paulo Roberto de Oliveira da Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay, Wan-Jui Lee, Uzay Kaymak:
Data-Driven Policy on Feasibility Determination for the Train Shunting Problem. ECML/PKDD (3) 2019: 719-734
[i1]
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  - journals/corr/abs-1907-04711
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Paulo R. de O. da Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay, Wan-Jui Lee, Uzay Kaymak:
Data-driven Policy on Feasibility Determination for the Train Shunting Problem. CoRR abs/1907.04711 (2019)
2018
[c23]
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Evertjan Peer, Vlado Menkovski, Yingqian Zhang, Wan-Jui Lee:
Shunting Trains with Deep Reinforcement Learning. SMC 2018: 3063-3068
2017
[c22]
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Wan-Jui Lee:
Contextual Air Leakage Detection in Train Braking Pipes. IEA/AIE (2) 2017: 191-200
2012
[j5]
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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)
2011
[c21]
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Wan-Jui Lee, Robert P. W. Duin, Marco Loog:
Generalized Augmentation of Multiple Kernels. MCS 2011: 116-125
[c20]
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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
2010
[c19]
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Wan-Jui Lee, Robert P. W. Duin, Alessandro Ibba, Marco Loog:
An experimental study on combining Euclidean distances. CIP 2010: 304-309
[c18]
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Alessandro Ibba, Robert P. W. Duin, Wan-Jui Lee:
A Study on Combining Sets of Differently Measured Dissimilarities. ICPR 2010: 3360-3363
[c17]
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Wan-Jui Lee, Robert P. W. Duin, Horst Bunke:
Selecting Structural Base Classifiers for Graph-Based Multiple Classifier Systems. MCS 2010: 155-164
[c16]
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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

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2009
[c15]
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Wan-Jui Lee, Robert P. W. Duin:
A Labelled Graph Based Multiple Classifier System. MCS 2009: 201-210
2008
[j4]
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Wan-Jui Lee, Jun-Shih Chung, Chen-Sen Ouyang, Shie-Jue Lee:
Vector Quantization of Images Using a Fuzzy Clustering Method. Cybern. Syst. 39(1): 45-60 (2008)
[j3]
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Wan-Jui Lee, Jung-Yi Jiang, Shie-Jue Lee:
Mining fuzzy periodic association rules. Data Knowl. Eng. 65(3): 442-462 (2008)
[c14]
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Shih Ta Kuan, Bang Ye Wu, Wan-Jui Lee:
Finding Friend Groups in Blogosphere. AINA Workshops 2008: 1046-1050
[c13]
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Wan-Jui Lee, Robert P. W. Duin:
An Inexact Graph Comparison Approach in Joint Eigenspace. SSPR/SPR 2008: 35-44
[c12]
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Robert P. W. Duin, Elzbieta Pekalska, Artsiom Harol, Wan-Jui Lee, Horst Bunke:
On Euclidean Corrections for Non-Euclidean Dissimilarities. SSPR/SPR 2008: 551-561
2007
[c11]
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Wan-Jui Lee, Sergey Verzakov, Robert P. W. Duin:
Kernel Combination Versus Classifier Combination. MCS 2007: 22-31
2006
[c10]
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Jiun-Hau Wang, Wan-Jui Lee, Shie-Jue Lee:
A Kernel-Based Fuzzy Clustering Algorithm. ICICIC (1) 2006: 550-553
[c9]
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Chih-Cheng Yang, Wan-Jui Lee, Shie-Jue Lee:
Learning of Kernel Functions in Support Vector Machines. IJCNN 2006: 1150-1155
[c8]
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Yi-Chao Chan, Wan-Jui Lee, Shie-Jue Lee:
Estimating Parameters of Kernel Functions in Support Vector Learning. SMC 2006: 192-197
2005
[j2]
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Chen-Sen Ouyang, Wan-Jui Lee, Shie-Jue Lee:
A TSK-type neurofuzzy network approach to system modeling problems. IEEE Trans. Syst. Man Cybern. Part B 35(4): 751-767 (2005)
[c7]
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Jung-Yi Jiang, Wan-Jui Lee, Shie-Jue Lee:
Mining Calendar-Based Asynchronous Periodical Association Rules with Fuzzy Calendar Constraints. FUZZ-IEEE 2005: 773-778
2004
[j1]
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Wan-Jui Lee, Shie-Jue Lee:
Discovery of fuzzy temporal association rules. IEEE Trans. Syst. Man Cybern. Part B 34(6): 2330-2342 (2004)
[c6]
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Wan-Jui Lee, Shie-Jue Lee:
An Incremental Algorithm for Discovering Fuzzy Temporal Web Usage Patterns. International Conference on Internet Computing 2004: 90-96
[c5]
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Wan-Jui Lee, Jung-Yi Jiang, Shie-Jue Lee:
An efficient algorithm to discover calendar-based temporal association rules. SMC (4) 2004: 3122-3127
[c4]
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  - conf/time/LeeL04
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Wan-Jui Lee, Shie-Jue Lee:
Fuzzy Calendar Algebra and Its Applications to Data Mining. TIME 2004: 71-78
2003
[c3]
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  - conf/ideal/LeeL03a
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Wan-Jui Lee, Shie-Jue Lee:
An Efficient Mining Method for Incremental Updation in Large Databases. IDEAL 2003: 630-637
[c2]
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Wan-Jui Lee, Shie-Jue Lee:
A general mining method for incremental updation in large databases. SMC 2003: 1423-1428
2002
[c1]
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Wan-Jui Lee, Chen-Sen Ouyang, Shie-Jue Lee:
Constructing neuro-fuzzy systems with TSK fuzzy rules and hybrid SVD-based learning. FUZZ-IEEE 2002: 1174-1179

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