Unsupervised clustering based on a competitive cost function. - Marco Saerens (IJCNN, 1990)

Acoustic-articulatory inversion based on a neural controller of a vocal tract model. - Alain Soquet; Marco Saerens; Paul Jospa (SSW, 1990)

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

Linear and nonlinear prediction for speech recognition with hidden Markov models. - Marco Saerens; Hervé Bourlard (EUROSPEECH, 1993)

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

A neural network based, speaker independent, large vocabulary, continuous speech recognition system: the WERNICKE project. - 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; et al. (EUROSPEECH, 1993)

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

A continuous-time dynamic formulation of Viterbi algorithm for one-Gaussian-per-state hidden Markov models. - Marco Saerens (Speech Commun., 1993)

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

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

Hopfield net generation, encoding and classification of temporal trajectories. - Hugues Bersini; Marco Saerens; Luis Gonzalez Sotelino (IEEE Trans. Neural Networks, 1994)

Viterbi algorithm for acoustic vectors generated by a linear stochastic differential equation on each state. - Marco Saerens (ICASSP, 1995)

Design of a perceptron-like algorithm based on system identification techniques. - Marco Saerens (IEEE Trans. Neural Networks, 1995)

Non Mean Square Error Criteria for the Training of Learning Machines. - Marco Saerens (ICML, 1996)

Fuzzy adaptive control of a certain class of SISO discrete-time processes. - Jean-Michel Renders; Marco Saerens; Hugues Bersini (Fuzzy Sets Syst., 1997)

Building cost functions minimizing to some summary statistics. - Marco Saerens (IEEE Trans. Neural Networks Learn. Syst., 2000)

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. - Patrice Latinne; Marco Saerens; Christine Decaestecker (ICML, 2001)

Adjusting the Outputs of a Classifier to New a Priori Probabilities: A Simple Procedure. - Marco Saerens; Patrice Latinne; Christine Decaestecker (Neural Comput., 2002)

Any reasonable cost function can be used for a posteriori probability approximation. - Marco Saerens; Patrice Latinne; Christine Decaestecker (IEEE Trans. Neural Networks, 2002)

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

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

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

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

Web Recommendation System Based on a Markov-Chainmodel. - François Fouss; Stéphane Faulkner; Manuel Kolp; Alain Pirotte 001; Marco Saerens (ICEIS (4), 2005)

A Novel Way of Computing Similarities between Nodes of a Graph, with Application to Collaborative Recommendation. - François Fouss; Alain Pirotte 001; Marco Saerens (Web Intelligence, 2005)

HITS is Principal Components Analysis. - Marco Saerens; François Fouss (Web Intelligence, 2005)

Optimal Tuning of Continual Online Exploration in Reinforcement Learning. - Youssef Achbany; François Fouss; Luh Yen; Alain Pirotte 001; Marco Saerens (ICANN (1), 2006)

An Experimental Investigation of Graph Kernels on a Collaborative Recommendation Task. - François Fouss; Luh Yen; Alain Pirotte 001; Marco Saerens (ICDM, 2006)

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). - Marco Saerens (Fuzzy Sets Syst., 2006)

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

Dynamic Web Service Composition within a Service-Oriented Architecture. - Ivan Jureta; Stéphane Faulkner; Youssef Achbany; Marco Saerens (ICWS, 2007)

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

Random-Walk Computation of Similarities between Nodes of a Graph with Application to Collaborative Recommendation. - François Fouss; Alain Pirotte 001; Jean-Michel Renders; Marco Saerens (IEEE Trans. Knowl. Data Eng., 2007)

QL2, a simple reinforcement learning scheme for two-player zero-sum Markov games. - Benoît Frénay; Marco Saerens (ESANN, 2008)

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

Classification in Graphs using Discriminative Random Walks. - Jérôme Callut; Kevin Françoisse; Marco Saerens; Pierre Dupont (MLG@ICML, 2008)

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

Evaluating Performance of Recommender Systems: An Experimental Comparison. - François Fouss; Marco Saerens (Web Intelligence, 2008)

Tuning continual exploration in reinforcement learning: An optimality property of the Boltzmann strategy. - Youssef Achbany; François Fouss; Luh Yen; Alain Pirotte 001; Marco Saerens (Neurocomputing, 2008)

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

2S2, a simple reinforcement learning scheme for two-player zero-sum Markov games. - Benoît Frénay; Marco Saerens (Neurocomputing, 2009)

Randomized Shortest-Path Problems: Two Related Models. - Marco Saerens; Youssef Achbany; François Fouss; Luh Yen (Neural Comput., 2009)

Normalized Sum-over-Paths Edit Distances. - Silvia García-Díez; François Fouss; Masashi Shimbo; Marco Saerens (ICPR, 2010)

A probabilistic reputation model based on transaction ratings. - François Fouss; Youssef Achbany; Marco Saerens (Inf. Sci., 2010)

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

A continuous-state version of discrete randomized shortest-paths, with application to path planning. - Silvia García-Díez; Eric Vandenbussche; Marco Saerens (CDC/ECC, 2011)

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

A sum-over-paths extension of edit distances accounting for all sequence alignments. - Silvia García-Díez; François Fouss; Masashi Shimbo; Marco Saerens (Pattern Recognit., 2011)

Semi-supervised classification and betweenness computation on large, sparse, directed graphs. - Amin Mantrach; Nicolas van Zeebroeck; Pascal Francq; Masashi Shimbo; Hugues Bersini; Marco Saerens (Pattern Recognit., 2011)

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

Investigating the Effectiveness of Laplacian-Based Kernels in Hub Reduction. - Ikumi Suzuki; Kazuo Hara; Masashi Shimbo; Yuji Matsumoto 001; Marco Saerens (AAAI, 2012)

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

An experimental investigation of kernels on graphs for collaborative recommendation and semisupervised classification. - François Fouss; Kevin Françoisse; Luh Yen; Alain Pirotte 001; Marco Saerens (Neural Networks, 2012)

Centering Similarity Measures to Reduce Hubs. - Ikumi Suzuki; Kazuo Hara; Masashi Shimbo; Marco Saerens; Kenji Fukumizu (EMNLP, 2013)

A Graph-Based Approach to Skill Extraction from Text. - Ilkka Kivimäki; Alexander Panchenko; Adrien Dessy; Dries Verdegem; Pascal Francq; Hugues Bersini; Marco Saerens (TextGraphs@EMNLP, 2013)

A link-analysis-based discriminant analysis for exploring partially labeled graphs. - Kevin Françoisse; François Fouss; Marco Saerens (Pattern Recognit. Lett., 2013)

Rminimax: An Optimally Randomized MINIMAX Algorithm. - Silvia García-Díez; Jérôme Laforge; Marco Saerens (IEEE Trans. Cybern., 2013)

The Sum-over-Forests clustering. - Mathieu Senelle; Marco Saerens; François Fouss (ESANN, 2014)

Random walks based modularity: application to semi-supervised learning. - Robin Devooght; Amin Mantrach; Ilkka Kivimäki; Hugues Bersini; Alejandro Jaimes; Marco Saerens (WWW, 2014)

A time-based collective factorization for topic discovery and monitoring in news. - Carmen K. Vaca; Amin Mantrach; Alejandro Jaimes; Marco Saerens (WWW, 2014)

The Sum-over-Forests Density Index: Identifying Dense Regions in a Graph. - Mathieu Senelle; Silvia García-Díez; Amin Mantrach; Masashi Shimbo; Marco Saerens; François Fouss (IEEE Trans. Pattern Anal. Mach. Intell., 2014)

Semisupervised Classification Through the Bag-of-Paths Group Betweenness. - Bertrand Lebichot; Ilkka Kivimäki; Kevin Françoisse; Marco Saerens (IEEE Trans. Neural Networks Learn. Syst., 2014)

Two betweenness centrality measures based on Randomized Shortest Paths. - Ilkka Kivimäki; Bertrand Lebichot; Jari Saramäki; Marco Saerens (CoRR, 2015)

A graph-based, semi-supervised, credit card fraud detection system. - Bertrand Lebichot; Fabian Braun; Olivier Caelen; Marco Saerens (COMPLEX NETWORKS, 2016)

Comparison of Graph Node Distances on Clustering Tasks. - Felix Sommer; François Fouss; Marco Saerens (ICANN (1), 2016)

Combining Manual and Automatic Prosodic Annotation for Expressive Speech Synthesis. - Sandrine Brognaux; Thomas François; Marco Saerens (LREC, 2016)

Modularity-Driven Kernel k-means for Community Detection. - Felix Sommer; François Fouss; Marco Saerens (ICANN (2), 2017)

A bag-of-paths framework for network data analysis. - Kevin Françoisse; Ilkka Kivimäki; Amin Mantrach; Fabrice Rossi; Marco Saerens (Neural Networks, 2017)

A Constrained Randomized Shortest-Paths Framework for Optimal Exploration. - Bertrand Lebichot; Guillaume Guex; Ilkka Kivimäki; Marco Saerens (CoRR, 2018)

A bag-of-paths node criticality measure. - Bertrand Lebichot; Marco Saerens (Neurocomputing, 2018)

Graph-Based Fraud Detection with the Free Energy Distance. - Sylvain Courtain; Bertrand Lebichot; Ilkka Kivimäki; Marco Saerens (COMPLEX NETWORKS (2), 2019)

Covariance and Correlation Kernels on a Graph in the Generalized Bag-of-Paths Formalism. - Guillaume Guex; Sylvain Courtain; Marco Saerens (CoRR, 2019)

Randomized optimal transport on a graph: framework and new distance measures. - Guillaume Guex; Ilkka Kivimäki; Marco Saerens (Netw. Sci., 2019)

Maximum likelihood estimation for randomized shortest paths with trajectory data. - Ilkka Kivimäki; Bram Van Moorter; Manuela Panzacchi; Jari Saramäki; Marco Saerens (J. Complex Networks, 2020)

An experimental study of graph-based semi-supervised classification with additional node information. - Bertrand Lebichot; Marco Saerens (Knowl. Inf. Syst., 2020)

A Simple Extension of the Bag-of-Paths Model Weighting Path Lengths by a Poisson Distribution. - Sylvain Courtain; Marco Saerens (COMPLEX NETWORKS, 2021)

Covariance and correlation measures on a graph in a generalized bag-of-paths formalism. - Guillaume Guex; Sylvain Courtain; Marco Saerens (J. Complex Networks, 2021)

Sparse randomized shortest paths routing with Tsallis divergence regularization. - Pierre Leleux; Sylvain Courtain; Guillaume Guex; Marco Saerens (Data Min. Knowl. Discov., 2021)

Randomized shortest paths with net flows and capacity constraints. - Sylvain Courtain; Pierre Leleux; Ilkka Kivimäki; Guillaume Guex; Marco Saerens (Inf. Sci., 2021)

Maximum Entropy Logistic Regression for Demographic Parity in Supervised Classification. - Flore Vancompernolle Vromman; Sylvain Courtain; Pierre Leleux; Constantin de Schaetzen; Eve Beghein; Alexia Kneip; Marco Saerens (BNAIC/BENELEARN, 2023)

Relative entropy-regularized optimal transport on a graph: a new algorithm and an experimental comparison. - Sylvain Courtain; Guillaume Guex; Ilkka Kivimäki; Marco Saerens (Int. J. Mach. Learn. Cybern., 2023)

In-processing and post-processing strategies for balancing accuracy and sustainability in product recommendations. - Chloe Satinet; François Fouss; Marco Saerens; Pierre Leleux (Electron. Commer. Res. Appl., 2024)

Sparse randomized policies for Markov decision processes based on Tsallis divergence regularization. - Pierre Leleux; Bertrand Lebichot; Guillaume Guex; Marco Saerens (Knowl. Based Syst., 2024)

Calibration methods in imbalanced binary classification. - Théo Guilbert; Olivier Caelen; Andrei Chirita; Marco Saerens (Ann. Math. Artif. Intell., 2024)