Consulter le flux RSS

Publications

Affichage des publications 521 à 530 sur 1099 au total

Machine Learning

Subspace Co-clustering with Two-Way Graph Convolution

Subspace clustering aims to cluster high dimensional data lying in a union of low-dimensional subspaces. It has shown good results on the task of image clustering but text clustering, using documentterm matrices, proved more impervious to advances…

Chakib Fettal, Lazhar Labiod, Mohamed Nadif

CIKM '22: The 31st ACM International Conference on Information and Knowledge Management -

Life Sciences

Anxiety onset in adolescents: a machine-learning prediction

Abstract Recent longitudinal studies in youth have reported MRI correlates of prospective anxiety symptoms during adolescence, a vulnerable period for the onset of anxiety disorders. However, their predictive value has not been established…

Alice Chavanne, Marie Laure Paillère Martinot, Jani Penttilä, Yvonne Grimmer, Patricia Conrod, Argyris Stringaris, Betteke van Noort, Corinna Isensee, Andreas Becker, Tobias Banaschewski, Arun Bokde, Sylvane Desrivières, Herta Flor, Antoine Grigis, Hugh Garavan, Penny Gowland, Andreas Heinz, Rüdiger Brühl, Frauke Nees, Dimitri Papadopoulos Orfanos, Tomáš Paus, Luise Poustka, Sarah Hohmann, Sabina Millenet, Juliane Fröhner, Michael Smolka, Henrik Walter, Robert Whelan, Gunter Schumann, Jean-Luc Martinot, Eric Artiges, Semiha Aydin, Christine Bach, Alexis Barbot, Gareth Barker, Nadège Bordas, Zuleima Bricaud, Uli Bromberg, Ruediger Bruehl, Christian Büchel, Anna Cattrell, Tahmine Fadai, Irina Filippi, Vincent Frouin, André Galinowski, Jürgen Gallinat, Fanny Gollier Briand, Chantal Gourlan, Stella Guldner, Bernd Ittermann, Tianye Jia, Hervé Lemaitre, Jessica Massicotte, Ruben Miranda, Kathrin Müller, Charlotte Nymberg, Zdenka Pausova, Jean-Baptiste Poline, Jan Reuter, John Rogers, Barbara Ruggeri, Anna Sarvasmaa, Christine Schmäl, Maren Struve, Wolfgang Sommer, Hélène Vulser

Molecular Psychiatry -

Life Sciences

Correction: Arc controls alcohol cue relapse by a central amygdala mechanism

Roberto Pagano, Ahmad Salamian, Janusz Zielinski, Anna Beroun, Maria Nalberczak-Skóra, Edyta Skonieczna, Anna Cały, Nicole Tay, Tobias Banaschewski, Sylvane Desrivières, Antoine Grigis, Hugh Garavan, Andreas Heinz, Rüdiger Brühl, Jean-Luc Martinot, Marie-Laure Paillère Martinot, Eric Artiges, Frauke Nees, Dimitri Papadopoulos Orfanos, Luise Poustka, Sarah Hohmann, Juliane Fröhner, Michael Smolka, Nilakshi Vaidya, Henrik Walter, Robert Whelan, Katarzyna Kalita, Haruhiko Bito, Christian Müller, Gunter Schumann, Hiroyuki Okuno, Kasia Radwanska

Molecular Psychiatry -

Machine Learning

Efficient and Effective Optimal Transport-Based Biclustering

Bipartite graphs can be used to model a wide variety of dyadic information such as user-rating, document-term, and gene-disorder pairs. Biclustering is an extension of clustering to the underlying bipartite graph induced from this kind of data. In…

Chakib Fettal, Lazhar Labiod, Mohamed Nadif

Advances in Neural Information Processing Systems -

Computer Science

An effective strategy for churn prediction and customer profiling

Customer churn prediction and profiling are two major economic concerns for many companies. Different learning approaches have been proposed, however the a priori choice of the most suitable model to perform both tasks remains non-trivial as it is…

Louis Geiler, Séverine Affeldt, Mohamed Nadif

Data and Knowledge Engineering -

Computer Science

Unsupervised Domain Adaptation for Constraining Star Formation Histories

The prevalent paradigm of machine learning today is to use past observations to predict future ones. What if, however, we are interested in knowing the past given the present? This situation is indeed one that astronomers must contend with often. To…

Sankalp Gilda, Antoine de Mathelin, Sabine Bellstedt, Guillaume Richard

1st Annual AAAI Workshop on AI to Accelerate Science and Engineering (AI2ASE) -

Computer Science

Fast and Accurate Importance Weighting for Correcting Sample Bias

Bias in datasets can be very detrimental for appropriate statistical estimation. In response to this problem, importance weighting methods have been developed to match any biased distribution to its corresponding target unbiased distribution. The…

Antoine de Mathelin, Francois Deheeger, Mathilde Mougeot, Nicolas Vayatis

Joint European Conference on Machine Learning and Knowledge Discovery in Databases -