Marco Saerens

Kevin Françoisse, François Fouss, Marco Saerens: A link-analysis-based discriminant analysis for exploring partially labeled graphs. Pattern Recognition Letters 34(2): 146-154 (2013)

Mathieu Senelle, Silvia García-Díez, Amin Mantrach, Masashi Shimbo, Marco Saerens, François Fouss: The Sum-over-Forests density index: identifying dense regions in a graph. CoRR abs/1301.0725 (2013)

François Fouss, Kevin Françoisse, Luh Yen, Alain Pirotte, Marco Saerens: An experimental investigation of kernels on graphs for collaborative recommendation and semisupervised classification. Neural Networks 31: 53-72 (2012)

Ikumi Suzuki, Kazuo Hara, Masashi Shimbo, Yuji Matsumoto, Marco Saerens: Investigating the Effectiveness of Laplacian-Based Kernels in Hub Reduction. AAAI 2012

Bertrand Lebichot, Ilkka Kivimäki, Kevin Françoisse, Marco Saerens: Semi-Supervised Classification Through the Bag-of-Paths Group Betweenness. CoRR abs/1210.4276 (2012)

Silvia García-Díez, François Fouss, Masashi Shimbo, Marco Saerens: A sum-over-paths extension of edit distances accounting for all sequence alignments. Pattern Recognition 44(6): 1172-1182 (2011)

Amin Mantrach, Nicolas van Zeebroeck, Pascal Francq, Masashi Shimbo, Hugues Bersini, Marco Saerens: Semi-supervised classification and betweenness computation on large, sparse, directed graphs. Pattern Recognition 44(6): 1212-1224 (2011)

Luh Yen, Marco Saerens, François Fouss: A Link Analysis Extension of Correspondence Analysis for Mining Relational Databases. IEEE Trans. Knowl. Data Eng. 23(4): 481-495 (2011)

Silvia García-Díez, Eric Vandenbussche, Marco Saerens: A continuous-state version of discrete randomized shortest-paths, with application to path planning. CDC-ECE 2011: 6570-6577

Silvia García-Díez, Marco Saerens, Mathieu Senelle, François Fouss: A simple-cycles weighted kernel based on harmony structure for similarity retrieval. ISMIR 2011: 61-66

François Fouss, Youssef Achbany, Marco Saerens: A probabilistic reputation model based on transaction ratings. Inf. Sci. 180(11): 2095-2123 (2010)

Amin Mantrach, Luh Yen, Jérôme Callut, Kevin Françoisse, Masashi Shimbo, Marco Saerens: The Sum-over-Paths Covariance Kernel: A Novel Covariance Measure between Nodes of a Directed Graph. IEEE Trans. Pattern Anal. Mach. Intell. 32(6): 1112-1126 (2010)

Silvia García-Díez, François Fouss, Masashi Shimbo, Marco Saerens: Normalized Sum-over-Paths Edit Distances. ICPR 2010: 1044-1047

Luh Yen, François Fouss, Christine Decaestecker, Pascal Francq, Marco Saerens: Graph nodes clustering with the sigmoid commute-time kernel: A comparative study. Data Knowl. Eng. 68(3): 338-361 (2009)

Benoît Frénay, Marco Saerens: 2S₂, a simple reinforcement learning scheme for two-player zero-sum Markov games. Neurocomputing 72(7-9): 1494-1507 (2009)

Marco Saerens, Youssef Achbany, François Fouss, Luh Yen: Randomized Shortest-Path Problems: Two Related Models. Neural Computation 21(8): 2363-2404 (2009)

Benoît Frénay, Marco Saerens: QL2, a simple reinforcement learning scheme for two-player zero-sum Markov games. ESANN 2008: 137-142

Luh Yen, Marco Saerens, Amin Mantrach, Masashi Shimbo: A family of dissimilarity measures between nodes generalizing both the shortest-path and the commute-time distances. KDD 2008: 785-793

Jérôme Callut, Kevin Françoisse, Marco Saerens, Pierre Dupont: Semi-supervised Classification from Discriminative Random Walks. ECML/PKDD (1) 2008: 162-177

François Fouss, Marco Saerens: Evaluating Performance of Recommender Systems: An Experimental Comparison. Web Intelligence 2008: 735-738

François Fouss, Alain Pirotte, Jean-Michel Renders, Marco Saerens: Random-Walk Computation of Similarities between Nodes of a Graph with Application to Collaborative Recommendation. IEEE Trans. Knowl. Data Eng. 19(3): 355-369 (2007)

Ivan Jureta, Stéphane Faulkner, Youssef Achbany, Marco Saerens: Dynamic task allocation within an open service-oriented MAS architecture. AAMAS 2007: 206

Ivan Jureta, Stéphane Faulkner, Youssef Achbany, Marco Saerens: Dynamic Web Service Composition within a Service-Oriented Architecture. ICWS 2007: 304-311

Luh Yen, François Fouss, Christine Decaestecker, Pascal Francq, Marco Saerens: Graph Nodes Clustering Based on the Commute-Time Kernel. PAKDD 2007: 1037-1045

Marco Saerens: Hung T. Nguyen, Nadipuram R. Prasad, Carol L. Walker and Elbert A. Walker, Editors, A First Course in Fuzzy 3 and Neural Control, Chapman & Hall/CRC Press (2003). Fuzzy Sets and Systems 157(16): 2286-2288 (2006)

Youssef Achbany, François Fouss, Luh Yen, Alain Pirotte, Marco Saerens: Optimal Tuning of Continual Online Exploration in Reinforcement Learning. ICANN (1) 2006: 790-800

François Fouss, Luh Yen, Alain Pirotte, Marco Saerens: An Experimental Investigation of Graph Kernels on a Collaborative Recommendation Task. ICDM 2006: 863-868

Luh Yen, Denis Vanvyve, Fabien Wouters, François Fouss, Michel Verleysen, Marco Saerens: clustering using a random walk based distance measure. ESANN 2005: 317-324

François Fouss, Stéphane Faulkner, Manuel Kolp, Alain Pirotte, Marco Saerens: Web Recommendation System Based on a Markov-Chainmodel. ICEIS (4) 2005: 56-63

François Fouss, Alain Pirotte, Marco Saerens: A Novel Way of Computing Similarities between Nodes of a Graph, with Application to Collaborative Recommendation. Web Intelligence 2005: 550-556

Marco Saerens, François Fouss: HITS is Principal Components Analysis. Web Intelligence 2005: 782-785

Marco Saerens, François Fouss, Luh Yen, Pierre Dupont: The Principal Components Analysis of a Graph, and Its Relationships to Spectral Clustering. ECML 2004: 371-383

Marco Saerens, François Fouss: Yet Another Method for Combining Classifiers Outputs: A Maximum Entropy Approach. Multiple Classifier Systems 2004: 82-91

François Fouss, Marco Saerens, Jean-Michel Renders: Links Between Kleinberg's Hubs and Authorities, Correspondence Analysis, and Markov Chains. ICDM 2003: 521-524

Marco Saerens, Patrice Latinne, Christine Decaestecker: Adjusting the Outputs of a Classifier to New a Priori Probabilities: A Simple Procedure. Neural Computation 14(1): 21-41 (2002)

Marco Saerens, Patrice Latinne, Christine Decaestecker: Any reasonable cost function can be used for a posteriori probability approximation. IEEE Transactions on Neural Networks 13(5): 1204-1210 (2002)

Patrice Latinne, Marco Saerens, Christine Decaestecker: Adjusting the Outputs of a Classifier to New a Priori Probabilities May Significantly Improve Classification Accuracy: Evidence from a multi-class problem in remote sensing. ICML 2001: 298-305

Marco Saerens: Building cost functions minimizing to some summary statistics. IEEE Trans. Neural Netw. Learning Syst. 11(6): 1263-1271 (2000)

Marco Saerens: Non Mean Square Error Criteria for the Training of Learning Machines. ICML 1996: 427-434

Marco Saerens: Design of a perceptron-like algorithm based on system identification techniques. IEEE Trans. Neural Netw. Learning Syst. 6(2): 504-506 (1995)

Luis Gonzalez Sotelino, Marco Saerens, Hugues Bersini: Classification of temporal trajectories by continuous-time recurrent nets. Neural Networks 7(5): 767-776 (1994)

Alain Soquet, Marco Saerens: A comparison of different acoustic and articulatory representations for the determination of place of articulation of plosives. ICSLP 1994

Marco Saerens: A continuous-time dynamic formulation of Viterbi algorithm for one-Gaussian-per-state hidden Markov models. Speech Communication 12(4): 321-333 (1993)

Jean-Michel Renders, Hugues Bersini, Marco Saerens: Adaptive NeuroControl: How Black Box and Simple can it be. ICML 1993: 260-267

Marco Saerens, Hervé Bourlard: Linear and nonlinear prediction for speech recognition with hidden Markov models. EUROSPEECH 1993

Hervé Bourlard, Jean-Marc Boite, Bart D'hoore, Marco Saerens: Performance comparison of hidden Markov models and neural networks for task dependent and independent isolated word recognition. EUROSPEECH 1993

Tony Robinson, Luís B. Almeida, Jean-Marc Boite, Hervé Bourlard, Frank Fallside, Mike Hochberg, Dan J. Kershaw, Phil Kohn, Yochai Konig, Nelson Morgan, João Paulo Neto, Steve Renals, Marco Saerens, Chuck Wooters: A neural network based, speaker independent, large vocabulary, continuous speech recognition system: the WERNICKE project. EUROSPEECH 1993

Marco Saerens: Hidden Markov models assuming a continuous-time dynamic emission of acoustic vectors. EUROSPEECH 1993