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A soft k-segments algorithm for principal curvesInternational Conference on Artificial Neural Networks, Aug 2001, Vienna, Austria. pp.450-456, ⟨10.1007/3-540-44668-0_63⟩
Conference papers
inria-00321506v1
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Gaussian mixture learning from noisy data[Technical Report] IAS-UVA-04, 2004, pp.6
Reports
inria-00321483v2
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Non-linear CCA and PCA by alignment of local modelsSeventeenth Annual Conference on Neural Information Processing Systems (NIPS '03), Dec 2003, Vancouver, Canada. pp.297--304
Conference papers
inria-00321485v2
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A k-segments algorithm for finding principal curvesPattern Recognition Letters, 2002, 23 (8), pp.1009--1017. ⟨10.1016/S0167-8655(02)00032-6⟩
Journal articles
inria-00321497v1
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Coordinating principal component analyzersInternational Conference on Artificial Neural Networks (ICANN '02), Aug 2002, Madrid, Spain. ⟨10.1007/3-540-46084-5_148⟩
Conference papers
inria-00321498v1
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Gaussian fields for semi-supervised regression and correspondence learningPattern Recognition, 2006, 39, pp.1864 - 1875. ⟨10.1016/j.patcog.2006.04.011⟩
Journal articles
inria-00321133v1
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Condensing the omics fog of microbial communitiesTrends in Microbiology, 2013, 21 (7), pp.325-333. ⟨10.1016/j.tim.2013.04.009⟩
Journal articles
hal-02329342v1
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Accelerated greedy mixture learningBenelearn: Annual Machine Learning Conference of Belgium and the Netherlands, Jan 2004, Brussels, Belgium
Conference papers
inria-00321482v2
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A variational EM algorithm for large-scale mixture modeling9th Annual Conference of the Advanced School for Computing and Imaging (ASCI '03), Jun 2003, Heijen, Netherlands. pp.136--143
Conference papers
inria-00321486v2
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A k-segments algorithm for finding principal curves[Technical Report] IAS-UVA-00-11, 2000, pp.12
Reports
inria-00321517v1
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Procrustes analysis to coordinate mixtures of probabilistic principal component analyzers[Technical Report] IAS-UVA-02, 2002, pp.18
Reports
inria-00321503v1
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Greedy Gaussian mixture learning for texture segmentationICANN Workshop on Kernel and Subspace Methods for Computer Vision, Aug 2001, Wien, Austria. pp.37--46
Conference papers
inria-00321513v1
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Accelerated EM-based clustering of large data setsData Mining and Knowledge Discovery, 2006, Data Mining and Knowledge Discovery, 13 (3), pp.291-307. ⟨10.1007/s10618-005-0033-3⟩
Journal articles
inria-00321022v2
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Community-integrated omics links dominance of a microbial generalist to fine-tuned resource usageNature Communications, 2014, 5 (1), ⟨10.1038/ncomms6603⟩
Journal articles
hal-02329310v1
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The generative self-organizing map: a probabilistic generalization of Kohonen's SOM[Technical Report] IAS-UVA-02-03, 2002
Reports
inria-00321505v1
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Efficient greedy learning of Gaussian mixtures[Technical Report] IAS-UVA-01-10, 2001, pp.22
Reports
inria-00321507v1
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Non-linear feature extraction by the coordination of mixture models9th Annual Conference of the Advanced School for Computing and Imaging (ASCI '03), Jun 2003, Heijen, Netherlands. pp.287--293
Conference papers
inria-00321490v2
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Self-organizing mixture modelsNeurocomputing, 2005, 63, pp.99--123. ⟨10.1016/j.neucom.2004.04.008⟩
Journal articles
inria-00321479v1
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Fast nonlinear dimensionality reduction with topology preserving networks10th Eurorean Symposium on Artificial Neural Networks (ESANN '02), Apr 2002, Bruges, Belgium
Conference papers
inria-00321500v1
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Self-organization by optimizing free-energy11th European Symposium on Artificial Neural Networks (ESANN '03), Apr 2003, Bruges, Belgium. pp.125-130
Conference papers
inria-00321491v2
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The global k-means clustering algorithmPattern Recognition, 2003, 36 (2), pp.451 - 461. ⟨10.1016/S0031-3203(02)00060-2⟩
Journal articles
inria-00321493v1
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Efficient greedy learning of Gaussian mixture modelsNeural Computation, 2003, 15 (2), pp.469-485. ⟨10.1162/089976603762553004⟩
Journal articles
inria-00321487v1
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Locally linear generative topographic mappingBenelearn: Annual Machine Learning Conference of Belgium and the Netherlands, Dec 2002, Utrecht, Netherlands. pp.79--86
Conference papers
inria-00321501v1
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Efficient greedy learning of Gaussian mixturesThe 13th Belgian-Dutch Conference on Artificial Intelligence (BNAIC'01), Oct 2001, Amsterdam, Netherlands. pp.251--258
Conference papers
inria-00321510v1
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The global k-means clustering algorithm[Technical Report] IAS-UVA-01-02, 2001, pp.12
Reports
inria-00321515v1
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Semi-supervised learning with Gaussian fields[Technical Report] IAS-UVA-05, 2005, pp.20
Reports
inria-00321480v2
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