| 2009 |
47 | | David Catteeuw,
Bernard Manderick:
Learning in the time-dependent minority game.
GECCO (Companion) 2009: 2011-2016 |
46 | | 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 |
45 | | Yifei Chen,
Feng Liu,
Bernard Manderick:
Evaluating and Comparing Biomedical Term Identification Systems.
ICIC (1) 2008: 970-977 |
44 | | 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 |
43 | | 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 |
42 | | Stijn Meganck,
Philippe Leray,
Bernard Manderick:
Causal Graphical Models with Latent Variables: Learning and Inference.
ECSQARU 2007: 5-16 |
41 | | Feng Liu,
Yifei Chen,
Bernard Manderick:
Named Entity Recognition in Biomedical Literature Using Two-Layer Support Vector Machines.
ICEIS (2) 2007: 39-48 |
40 | | 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 |
39 | | Sam Maes,
Stijn Meganck,
Bernard Manderick:
Inference in multi-agent causal models.
Int. J. Approx. Reasoning 46(2): 274-299 (2007) |
| 2006 |
38 | | Stijn Meganck,
Philippe Leray,
Bernard Manderick:
Learning Causal Bayesian Networks from Observations and Experiments: A Decision Theoretic Approach.
MDAI 2006: 58-69 |
37 | | Stijn Meganck,
Sam Maes,
Philippe Leray,
Bernard Manderick:
Learning Semi-Markovian Causal Models using Experiments.
Probabilistic Graphical Models 2006: 195-206 |
| 2005 |
36 | | 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 |
35 | | Sam Maes,
Stijn Meganck,
Bernard Manderick:
Identification of Causal Effects in Multi-Agent Causal Models.
Artificial Intelligence and Applications 2005: 178-182 |
34 | | Bram Vanschoenwinkel,
Bernard Manderick:
Context-sensitive Kernel Functions: A Comparison Between Different Context Weights.
BNAIC 2005: 283-290 |
33 | | Peter Waiganjo Wagascha,
Bernard Manderick,
Maina Muuro:
On Support Vector and Relevance Vector Machines.
BNAIC 2005: 297-304 |
32 | | Sam Maes,
Stijn Meganck,
Bernard Manderick:
Causal Inference in Multi-Agent Causal Models.
BNAIC 2005: 367-368 |
31 | | Stijn Meganck,
Sam Maes,
Bernard Manderick,
Philippe Leray:
A Learning Algorithm for Multi-Agent Causal Models.
EUMAS 2005: 190-201 |
30 | | Sam Maes,
Stijn Meganck,
Bernard Manderick:
Identification in Chain Multi-Agent Causal Models.
FLAIRS Conference 2005: 791-792 |
29 | | Stijn Meganck,
Sam Maes,
Bernard Manderick,
Philippe Leray:
Distributed learning of Multi-Agent Causal Models.
IAT 2005: 285-288 |
28 | | Bram Vanschoenwinkel,
Feng Liu,
Bernard Manderick:
Context-Sensitive Kernel Functions: A Distance Function Viewpoint.
ICMLC 2005: 861-870 |
| 2004 |
27 | | 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 |
26 | | Piet van Remortel,
Bernard Manderick,
Tom Lenaerts:
Gene Interaction and Modularisation in a Model for Gene-Regulated Development.
Evolvable Hardware 2004: 253-260 |
| 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 |