Bernard Manderick

	2011
54		David Catteeuw, Bernard Manderick: Heterogeneous Populations of Learning Agents in the Minority Game. ALA 2011: 100-113
53		Yifei Chen, Feng Liu, Bernard Manderick: A machine learning-based system to normalise gene mentions to unique database identifiers. IJDMB 5(6): 640-660 (2011)
	2010
52		Ruben Hillewaere, Bernard Manderick, Darrell Conklin: String Quartet Classification with Monophonic Models. ISMIR 2010: 537-542
51		Yifei Chen, Feng Liu, Bernard Manderick: BioLMiner System: Interaction Normalization Task and Interaction Pair Task in the BioCreative II.5 Challenge. IEEE/ACM Trans. Comput. Biology Bioinform. 7(3): 428-441 (2010)
	2009
50		David Catteeuw, Bernard Manderick: Learning in Minority Games with Multiple Resources. ECAL (2) 2009: 326-333
49		David Catteeuw, Bernard Manderick: Learning in the time-dependent minority game. GECCO (Companion) 2009: 2011-2016
48		Ruben Hillewaere, Bernard Manderick, Darrell Conklin: Global Feature Versus Event Models for Folk Song Classification. ISMIR 2009: 729-734
47		Yifei Chen, Feng Liu, Bram Vanschoenwinkel, Bernard Manderick: Splice Site Prediction using Support Vector Machines with Context-Sensitive Kernel Functions. J. UCS 15(13): 2528-2546 (2009)
	2008
46		Yifei Chen, Feng Liu, Bernard Manderick: Evaluating and Comparing Biomedical Term Identification Systems. ICIC (1) 2008: 970-977
45		Philippe Leray, Stijn Meganck, Sam Maes, Bernard Manderick: Causal Graphical Models with Latent Variables: Learning and Inference. Innovations in Bayesian Networks 2008: 219-249
	2007
44		Yifei Chen, Feng Liu, Bernard Manderick: Improving the Performance of Gene Mention Recognition System using Reformed Lexicon-based Support Vector Machine. DMIN 2007: 228-234
43		Stijn Meganck, Philippe Leray, Bernard Manderick: Causal Graphical Models with Latent Variables: Learning and Inference. ECSQARU 2007: 5-16
42		Feng Liu, Yifei Chen, Bernard Manderick: Named Entity Recognition in Biomedical Literature Using Two-Layer Support Vector Machines. ICEIS (2) 2007: 39-48
41		Feng Liu, Yifei Chen, Bernard Manderick: Named Entity Recognition in Biomedical Literature: A Comparison of Support Vector Machines and Conditional Random Fields. ICEIS (Selected Papers) 2007: 137-147
40		Sam Maes, Stijn Meganck, Bernard Manderick: Inference in multi-agent causal models. Int. J. Approx. Reasoning 46(2): 274-299 (2007)
	2006
39		Stijn Meganck, Philippe Leray, Bernard Manderick: Learning Causal Bayesian Networks from Observations and Experiments: A Decision Theoretic Approach. MDAI 2006: 58-69
38		Stijn Meganck, Sam Maes, Philippe Leray, Bernard Manderick: Learning Semi-Markovian Causal Models using Experiments. Probabilistic Graphical Models 2006: 195-206
	2005
37		Katja Verbeeck, Karl Tuyls, Ann Nowé, Bernard Manderick, Bart Kuijpers: BNAIC 2005 - Proceedings of the Seventeenth Belgium-Netherlands Conference on Artificial Intelligence, Brussels, Belgium, October 17-18, 2005 Koninklijke Vlaamse Academie van Belie voor Wetenschappen en Kunsten 2005
36		Sam Maes, Stijn Meganck, Bernard Manderick: Identification of Causal Effects in Multi-Agent Causal Models. Artificial Intelligence and Applications 2005: 178-182
35		Bram Vanschoenwinkel, Bernard Manderick: Context-sensitive Kernel Functions: A Comparison Between Different Context Weights. BNAIC 2005: 283-290
34		Peter Waiganjo Wagascha, Bernard Manderick, Maina Muuro: On Support Vector and Relevance Vector Machines. BNAIC 2005: 297-304
33		Sam Maes, Stijn Meganck, Bernard Manderick: Causal Inference in Multi-Agent Causal Models. BNAIC 2005: 367-368
32		Stijn Meganck, Sam Maes, Bernard Manderick, Philippe Leray: A Learning Algorithm for Multi-Agent Causal Models. EUMAS 2005: 190-201
31		Sam Maes, Stijn Meganck, Bernard Manderick: Identification in Chain Multi-Agent Causal Models. FLAIRS Conference 2005: 791-792
30		Stijn Meganck, Sam Maes, Bernard Manderick, Philippe Leray: Distributed learning of Multi-Agent Causal Models. IAT 2005: 285-288
29		Bram Vanschoenwinkel, Feng Liu, Bernard Manderick: Context-Sensitive Kernel Functions: A Distance Function Viewpoint. ICMLC 2005: 861-870
	2004
28		Bram Vanschoenwinkel, Bernard Manderick: Appropriate Kernel Functions for Support Vector Machine Learning with Sequences of Symbolic Data. Deterministic and Statistical Methods in Machine Learning 2004: 256-280
27		Piet van Remortel, Bernard Manderick, Tom Lenaerts: Gene Interaction and Modularisation in a Model for Gene-Regulated Development. Evolvable Hardware 2004: 253-260
26		Bram Vanschoenwinkel, Bernard Manderick: Substitution matrix based kernel functions for protein secondary structure prediction. ICMLA 2004: 388-396
	2003
25		Karl Tuyls, Dries Heytens, Ann Nowé, Bernard Manderick: Extended Replicator Dynamics as a Key to Reinforcement Learning in Multi-agent Systems. ECML 2003: 421-431
24		Sam Maes, Joke Reumers, Bernard Manderick: Identifiability of Causal Effects in a Multi-Agent Causal Model. IAT 2003: 605-608
23		Piet van Remortel, Johan Ceuppens, Anne Defaweux, Tom Lenaerts, Bernard Manderick: Developmental Effects on Tuneable Fitness Landscapes. ICES 2003: 117-128
22		Bram Vanschoenwinkel, Bernard Manderick: A Weighted Polynomial Information Gain Kernel for Resolving Prepositional Phrase Attachment Ambiguities with Support Vector Machines. IJCAI 2003: 133-140
21		Thomas Hamelryck, Bernard Manderick: PDB file parser and structure class implemented in Python. Bioinformatics 19(17): 2308-2310 (2003)
	2002
20		Piet van Remortel, Tom Lenaerts, Bernard Manderick: Lineage and Induction in the Development of Evolved Genotypes for Non-uniform 2D CAs. Australian Joint Conference on Artificial Intelligence 2002: 321-332
19		Piet van Remortel, Tom Lenaerts, Bernard Manderick: The Robustness of Small Developped SBlock Circuits Using Different Clocking Schemes. Evolvable Hardware 2002: 26-35
18		Tom Lenaerts, Anne Defaweux, Piet van Remortel, Bernard Manderick: An Individual-based Approach To Multi-level Selection. GECCO 2002: 136
17		Tom Lenaerts, Anne Defaweux, Piet van Remortel, Bernard Manderick: Evaluation of a Simple Multi-Level Selection Model. GECCO Late Breaking Papers 2002: 323-329
16		Karl Tuyls, Sam Maes, Bernard Manderick: Q-Learning in Simulated Robotic Soccer - Large State Spaces and Incomplete Information. ICMLA 2002: 226-232
15		Karl Tuyls, Sam Maes, Bernard Manderick: Reinforcement Learning in Large State Spaces. RoboCup 2002: 319-326
	2001
14		Tom Lenaerts, Anne Defaweux, P. Beyens, Bernard Manderick: Transitions in a Simple Evolutionary Model. ECAL 2001: 436-439
	1998
13		Tom Lenaerts, Bernard Manderick: Building a Genetic Programming Framework: The Added-Value of Design Patterns. EuroGP 1998: 196-208
	1997
12		Ian Frank, Bernard Manderick, Tetsuya Higuchi: Recent Advances in Evolvable Systems - ICES 96 (International Conference on Evolvable Systems). Evolutionary Computation 5(1): 105-114 (1997)
	1996
11		Bernard Manderick, Tetsuya Higuchi: Evolvable Hardware: An Outlook. ICES 1996: 305-311
10		Piet Spiessens, Bernard Manderick: Finding Optimal Representations Using the Crossover Correlation Coefficient. SBIA 1996: 91-100
	1995
9		Wim Hordijk, Bernard Manderick: The Usefulness of Recombination. ECAL 1995: 908-919
8		Tetsuya Higuchi, Masaya Iwata, Isamu Kajitani, Hitoshi Iba, Yuji Hirao, Tatsumi Furuya, Bernard Manderick: Evolvable Hardware and Its Applications to Pattern Recognition and Fault-Tolerant Systems. Towards Evolvable Hardware 1995: 118-135
	1994
7		Tetsuya Higuchi, Hitoshi Iba, Bernard Manderick: Applying Evolvable Hardware to Autonomous Agents. PPSN 1994: 524-533
6		Hiroaki Inayoshi, Bernard Manderick: The Weighted Graph Bi-Partitioning Problem: A Look at GA Performance. PPSN 1994: 617-625
	1992
5		Reinhard Männer, Bernard Manderick: Parallel Problem Solving from Nature 2, PPSN-II, Brussels, Belgium, September 28-30, 1992 Elsevier 1992
	1991
4		Bernard Manderick, Mark K. de Weger, Piet Spiessens: The Genetic Algorithm and the Structure of the Fitness Landscape. ICGA 1991: 143-150
3		Piet Spiessens, Bernard Manderick: A Massively Parallel Genetic Algorithm: Implementation and First Analysis. ICGA 1991: 279-287
	1990
2		Bernard Manderick: Selectionist Categorization. PPSN 1990: 326-330
	1989
1		Bernard Manderick, Piet Spiessens: Fine-Grained Parallel Genetic Algorithms. ICGA 1989: 428-433

Coauthor Index

1	P. Beyens	[14]
2	David Catteeuw	[49] [50] [54]
3	Johan Ceuppens	[23]
4	Yifei Chen	[41] [42] [44] [46] [47] [51] [53]
5	Darrell Conklin	[48] [52]
6	Anne Defaweux	[14] [17] [18] [23]
7	Ian Frank	[12]
8	Tatsumi Furuya	[8]
9	Thomas Hamelryck	[21]
10	Dries Heytens	[25]
11	Tetsuya Higuchi	[7] [8] [11] [12]
12	Ruben Hillewaere	[48] [52]
13	Yuji Hirao	[8]
14	Wim Hordijk	[9]
15	Hitoshi Iba	[7] [8]
16	Hiroaki Inayoshi	[6]
17	Masaya Iwata	[8]
18	Isamu Kajitani	[8]
19	Bart Kuijpers	[37]
20	Tom Lenaerts	[13] [14] [17] [18] [19] [20] [23] [27]
21	Philippe Leray	[30] [32] [38] [39] [43] [45]
22	Feng Liu	[29] [41] [42] [44] [46] [47] [51] [53]
23	Sam Maes	[15] [16] [24] [30] [31] [32] [33] [36] [38] [40] [45]
24	Reinhard Männer	[5]
25	Stijn Meganck	[30] [31] [32] [33] [36] [38] [39] [40] [43] [45]
26	Maina Muuro	[34]
27	Ann Nowé	[25] [37]
28	Piet van Remortel	[17] [18] [19] [20] [23] [27]
29	Joke Reumers	[24]
30	Piet Spiessens	[1] [3] [4] [10]
31	Karl Tuyls	[15] [16] [25] [37]
32	Bram Vanschoenwinkel	[22] [26] [28] [29] [35] [47]
33	Katja Verbeeck	[37]
34	Peter Waiganjo Wagascha	[34]
35	Mark K. de Weger	[4]

Colors in the list of coauthors

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