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Bernard Manderick
Person information
- affiliation: Vrije Universiteit Brussel, Artificial Intelligence Lab, Brussels, Belgium
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2020 – today
- 2023
- [c75]Bowen Liu
, Edna Milgo
Comparison of MCMC Adaptation Schemes: A Preliminary Empirical Study. GECCO Companion 2023: 303-306 - 2022
- [c74]Nixon K. Ronoh
Natural gradient evolution strategies for adaptive sampling. GECCO Companion 2022: 73-74
2010 – 2019
- 2017
- [c73]Edna Milgo, Nixon K. Ronoh, Peter Waiganjo Wagacha, Bernard Manderick:
Comparison of adaptive MCMC methods. ESANN 2017 - [c72]Edna Milgo
Adaptiveness of CMA based samplers. GECCO (Companion) 2017: 179-180 - 2016
- [j13]Dewan Md. Farid, M. Abdulla Al Mamun, Bernard Manderick, Ann Nowé:
An adaptive rule-based classifier for mining big biological data. Expert Syst. Appl. 64: 305-316 (2016) - [j12]David Catteeuw, Bernard Manderick
Honesty and deception in populations of selfish, adaptive individuals. Knowl. Eng. Rev. 31(1): 19-30 (2016) - [c71]Nixon K. Ronoh
Schemata Bandits for MAXSAT. GECCO (Companion) 2016: 1473-1474 - [c70]Dewan Md. Farid, Ann Nowé, Bernard Manderick:
Ensemble of Trees for Classifying High-Dimensional Imbalanced Genomic Data. IntelliSys (1) 2016: 172-187 - [c69]Isel Grau
Genomic Variant Classifier Tool. IntelliSys (1) 2016: 453-456 - 2015
- [j11]Yifei Chen, Hongjian Guo, Feng Liu, Bernard Manderick:
Improving protein-protein interaction article classification using biological domain knowledge. Int. J. Data Min. Bioinform. 12(2): 144-166 (2015) - [j10]Saba Q. Yahyaa, Madalina M. Drugan
Scalarized and Pareto Knowledge Gradient for Multi-objective Multi-armed Bandits. Trans. Comput. Collect. Intell. 20: 99-116 (2015) - [c68]Saba Q. Yahyaa, Madalina M. Drugan
Annealing linear scalarized based multi-objective multi-armed bandit algorithm. CEC 2015: 1738-1745 - [c67]Nixon K. Ronoh, Reuben Odoyo, Edna Milgo, Madalina M. Drugan, Bernard Manderick:
Bernoulli bandits: an empirical comparison. ESANN 2015 - [c66]Saba Q. Yahyaa, Bernard Manderick:
Thompson Sampling for Multi-Objective Multi-Armed Bandits Problem. ESANN 2015 - [c65]Saba Q. Yahyaa, Madalina M. Drugan, Bernard Manderick:
Thompson Sampling in the Adaptive Linear Scalarized Multi Objective Multi Armed Bandit. ICAART (2) 2015: 55-65 - [c64]Madalina M. Drugan, Bernard Manderick:
Exploration Versus Exploitation Trade-off in Infinite Horizon Pareto Multi-armed Bandits Algorithms. ICAART (2) 2015: 66-77 - [c63]Alejandro Baldominos, Pedro Isasi
Monte Carlo Schemata Searching for Physical Activity Recognition. INCoS 2015: 176-183 - 2014
- [j9]David Catteeuw, Bernard Manderick:
The limits and robustness of reinforcement learning in Lewis signalling games. Connect. Sci. 26(2): 161-177 (2014) - [c62]Madalina M. Drugan
Pareto Upper Confidence Bounds algorithms: An empirical study. ADPRL 2014: 1-8 - [c61]Saba Q. Yahyaa, Madalina M. Drugan
Annealing-pareto multi-objective multi-armed bandit algorithm. ADPRL 2014: 1-8 - [c60]Saba Q. Yahyaa, Madalina M. Drugan, Bernard Manderick:
Linear Scalarized Knowledge Gradient in the Multi-Objective Multi-Armed Bandits Problem. ESANN 2014 - [c59]David Catteeuw, The Anh Han
Evolution of honest signaling by social punishment. GECCO 2014: 153-160 - [c58]Saba Q. Yahyaa, Bernard Manderick:
Online Knowledge Gradient Exploration in an Unknown Environment. ICAART (1) 2014: 5-13 - [c57]Saba Q. Yahyaa, Madalina M. Drugan, Bernard Manderick:
Knowledge Gradient for Multi-objective Multi-armed Bandit Algorithms. ICAART (1) 2014: 74-83 - [c56]Saba Q. Yahyaa, Bernard Manderick:
Knowledge Gradient for Online Reinforcement Learning. ICAART (Revised Selected Papers) 2014: 103-118 - [c55]Saba Q. Yahyaa, Madalina M. Drugan
The scalarized multi-objective multi-armed bandit problem: An empirical study of its exploration vs. exploitation tradeoff. IJCNN 2014: 2290-2297 - [c54]Madalina M. Drugan
Schemata Bandits for Binary Encoded Combinatorial Optimisation Problems. SEAL 2014: 299-310 - 2013
- [c53]David Catteeuw, Bernard Manderick, The Anh Han
Evolutionary stability of honest signaling in finite populations. IEEE Congress on Evolutionary Computation 2013: 2864-2870 - [c52]Saba Q. Yahyaa, Bernard Manderick:
Empirical Evaluation of Shortest Path Gaussian Kernels over State Action Graphs. ICAART (2) 2013: 225-231 - [c51]Saba Q. Yahyaa, Bernard Manderick:
Knowledge Gradient Exploration in Online Least Squares Policy Iteration. ICAART (2) 2013: 263-269 - [c50]Eric Ayienga, Elisha Opiyo, Bernard Manderick, Okelo Odongo:
Game Theory and Learning at the Medium Access Control Layer for Distributed Radio Resource Sharing in Random Access Wireless Networks. ICAART (2) 2013: 535-542 - 2012
- [c49]Bernard Manderick, Saba Q. Yahyaa:
The Exploration vs Exploitation Trade-Off in Bandit Problems: An Empirical Study. ESANN 2012 - [c48]Ruben Hillewaere, Bernard Manderick, Darrell Conklin:
Alignment Methods for Folk Tune Classification. GfKl 2012: 369-377 - [c47]Ruben Hillewaere, Bernard Manderick, Darrell Conklin:
String Methods for Folk Tune Genre Classification. ISMIR 2012: 217-222 - 2011
- [j8]Yifei Chen, Feng Liu, Bernard Manderick:
A machine learning-based system to normalise gene mentions to unique database identifiers. Int. J. Data Min. Bioinform. 5(6): 640-660 (2011) - [c46]David Catteeuw, Bernard Manderick:
Heterogeneous Populations of Learning Agents in the Minority Game. ALA 2011: 100-113 - 2010
- [j7]Yifei Chen, Feng Liu, Bernard Manderick:
BioLMiner and the BioCreative II.5 challenge. BMC Bioinform. 11(S-5): P6 (2010) - [j6]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. Biol. Bioinform. 7(3): 428-441 (2010) - [c45]Ruben Hillewaere, Bernard Manderick, Darrell Conklin:
String Quartet Classification with Monophonic Models. ISMIR 2010: 537-542
2000 – 2009
- 2009
- [j5]Yifei Chen, Feng Liu, Bram Vanschoenwinkel, Bernard Manderick:
Splice Site Prediction using Support Vector Machines with Context-Sensitive Kernel Functions. J. Univers. Comput. Sci. 15(13): 2528-2546 (2009) - [c44]David Catteeuw, Bernard Manderick:
Learning in Minority Games with Multiple Resources. ECAL (2) 2009: 326-333 - [c43]David Catteeuw, Bernard Manderick:
Learning in the time-dependent minority game. GECCO (Companion) 2009: 2011-2016 - [c42]Ruben Hillewaere, Bernard Manderick, Darrell Conklin:
Global Feature Versus Event Models for Folk Song Classification. ISMIR 2009: 729-734 - 2008
- [c41]Yifei Chen, Feng Liu, Bernard Manderick:
Evaluating and Comparing Biomedical Term Identification Systems. ICIC (1) 2008: 970-977 - [p1]Philippe Leray
Causal Graphical Models with Latent Variables: Learning and Inference. Innovations in Bayesian Networks 2008: 219-249 - 2007
- [j4]Sam Maes, Stijn Meganck, Bernard Manderick:
Inference in multi-agent causal models. Int. J. Approx. Reason. 46(2): 274-299 (2007) - [c40]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 - [c39]Stijn Meganck, Philippe Leray, Bernard Manderick:
Causal Graphical Models with Latent Variables: Learning and Inference. ECSQARU 2007: 5-16 - [c38]Feng Liu, Yifei Chen, Bernard Manderick:
Named Entity Recognition in Biomedical Literature Using Two-Layer Support Vector Machines. ICEIS (2) 2007: 39-48 - [c37]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 - 2006
- [c36]Stijn Meganck, Philippe Leray
Learning Causal Bayesian Networks from Observations and Experiments: A Decision Theoretic Approach. MDAI 2006: 58-69 - [c35]Stijn Meganck, Sam Maes, Philippe Leray, Bernard Manderick:
Learning Semi-Markovian Causal Models using Experiments. Probabilistic Graphical Models 2006: 195-206 - 2005
- [c34]Sam Maes, Stijn Meganck, Bernard Manderick:
Identification of Causal Effects in Multi-Agent Causal Models. Artificial Intelligence and Applications 2005: 178-182 - [c33]Bram Vanschoenwinkel, Bernard Manderick:
Context-sensitive Kernel Functions: A Comparison Between Different Context Weights. BNAIC 2005: 283-290 - [c32]Peter Waiganjo Wagacha, Bernard Manderick, Maina Muuro:
On Support Vector and Relevance Vector Machines. BNAIC 2005: 297-304 - [c31]Sam Maes, Stijn Meganck, Bernard Manderick:
Causal Inference in Multi-Agent Causal Models. BNAIC 2005: 367-368 - [c30]Stijn Meganck, Sam Maes, Bernard Manderick, Philippe Leray:
A Learning Algorithm for Multi-Agent Causal Models. EUMAS 2005: 190-201 - [c29]Bernard Manderick, Sam Maes, Stijn Meganck:
Causal Inference in Multi-Agent Causal Models. EGC (Ateliers) 2005: 73-76 - [c28]Sam Maes, Stijn Meganck, Bernard Manderick:
Identification in Chain Multi-Agent Causal Models. FLAIRS 2005: 791-792 - [c27]Stijn Meganck, Sam Maes, Bernard Manderick, Philippe Leray
Distributed learning of Multi-Agent Causal Models. IAT 2005: 285-288 - [c26]Bram Vanschoenwinkel, Feng Liu, Bernard Manderick:
Context-Sensitive Kernel Functions: A Distance Function Viewpoint. ICMLC 2005: 861-870 - [e2]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 [contents] - 2004
- [j3]Karl Tuyls
An Evolutionary Game Theoretic Perspective on Learning in Multi-Agent Systems. Synth. 139(2): 297-330 (2004) - [c25]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 - [c24]Piet van Remortel, Bernard Manderick
Gene Interaction and Modularisation in a Model for Gene-Regulated Development. Evolvable Hardware 2004: 253-260 - [c23]Bram Vanschoenwinkel, Bernard Manderick:
Substitution matrix based kernel functions for protein secondary structure prediction. ICMLA 2004: 388-396 - 2003
- [j2]Thomas Hamelryck
PDB file parser and structure class implemented in Python. Bioinform. 19(17): 2308-2310 (2003) - [c22]Karl Tuyls
Extended Replicator Dynamics as a Key to Reinforcement Learning in Multi-agent Systems. ECML 2003: 421-431 - [c21]Sam Maes, Joke Reumers, Bernard Manderick:
Identifiability of Causal Effects in a Multi-Agent Causal Model. IAT 2003: 605-608 - [c20]Piet van Remortel, Johan Ceuppens, Anne Defaweux, Tom Lenaerts
Developmental Effects on Tuneable Fitness Landscapes. ICES 2003: 117-128 - [c19]Bram Vanschoenwinkel, Bernard Manderick:
A Weighted Polynomial Information Gain Kernel for Resolving Prepositional Phrase Attachment Ambiguities with Support Vector Machines. IJCAI 2003: 133-140 - 2002
- [c18]Piet van Remortel, Tom Lenaerts
Lineage and Induction in the Development of Evolved Genotypes for Non-uniform 2D CAs. Australian Joint Conference on Artificial Intelligence 2002: 321-332 - [c17]Piet van Remortel, Tom Lenaerts
The Robustness of Small Developped SBlock Circuits Using Different Clocking Schemes. Evolvable Hardware 2002: 26-35 - [c16]Tom Lenaerts, Anne Defaweux, Piet van Remortel, Bernard Manderick:
An Individual-based Approach To Multi-level Selection. GECCO 2002: 136 - [c15]Tom Lenaerts, Anne Defaweux, Piet van Remortel, Bernard Manderick:
Evaluation of a Simple Multi-Level Selection Model. GECCO Late Breaking Papers 2002: 323-329 - [c14]Karl Tuyls, Sam Maes, Bernard Manderick:
Q-Learning in Simulated Robotic Soccer - Large State Spaces and Incomplete Information. ICMLA 2002: 226-232 - [c13]Karl Tuyls
Reinforcement Learning in Large State Spaces. RoboCup 2002: 319-326 - 2001
- [c12]Tom Lenaerts
Transitions in a Simple Evolutionary Model. ECAL 2001: 436-439
1990 – 1999
- 1998
- [c11]Tom Lenaerts
Building a Genetic Programming Framework: The Added-Value of Design Patterns. EuroGP 1998: 196-208 - 1997
- [j1]Ian Frank, Bernard Manderick, Tetsuya Higuchi:
Recent Advances in Evolvable Systems - ICES 96 (International Conference on Evolvable Systems). Evol. Comput. 5(1): 105-114 (1997) - 1996
- [c10]Bernard Manderick, Tetsuya Higuchi:
Evolvable Hardware: An Outlook. ICES 1996: 305-311 - [c9]Piet Spiessens, Bernard Manderick:
Finding Optimal Representations Using the Crossover Correlation Coefficient. SBIA 1996: 91-100 - 1995
- [c8]Wim Hordijk, Bernard Manderick:
The Usefulness of Recombination. ECAL 1995: 908-919 - [c7]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
- [c6]Tetsuya Higuchi, Hitoshi Iba, Bernard Manderick:
Applying Evolvable Hardware to Autonomous Agents. PPSN 1994: 524-533 - [c5]Hiroaki Inayoshi, Bernard Manderick:
The Weighted Graph Bi-Partitioning Problem: A Look at GA Performance. PPSN 1994: 617-625 - 1992
- [e1]Reinhard Männer, Bernard Manderick:
Parallel Problem Solving from Nature 2, PPSN-II, Brussels, Belgium, September 28-30, 1992. Elsevier 1992 [contents] - 1991
- [c4]Bernard Manderick, Mark K. de Weger, Piet Spiessens:
The Genetic Algorithm and the Structure of the Fitness Landscape. ICGA 1991: 143-150 - [c3]Piet Spiessens, Bernard Manderick:
A Massively Parallel Genetic Algorithm: Implementation and First Analysis. ICGA 1991: 279-287 - 1990
- [c2]Bernard Manderick:
Selectionist Categorization. PPSN 1990: 326-330
1980 – 1989
- 1989
- [c1]Bernard Manderick, Piet Spiessens:
Fine-Grained Parallel Genetic Algorithms. ICGA 1989: 428-433
Coauthor Index
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