Filtrer vos résultats
- 17
- 6
- 10
- 10
- 2
- 1
- 17
- 9
- 7
- 1
- 1
- 1
- 2
- 2
- 5
- 2
- 3
- 4
- 1
- 3
- 23
- 8
- 7
- 5
- 5
- 4
- 4
- 4
- 2
- 2
- 2
- 2
- 2
- 2
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 23
- 12
- 4
- 3
- 3
- 3
- 2
- 2
- 2
- 2
- 2
- 2
- 2
- 2
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
- 1
23 résultats
|
|
|
triés par
|
|
|
Fast Optimal Transport Averaging of Neuroimaging DataInformation Processing in Medical Imaging (IPMI), Jun 2015, Isle of Skye, United Kingdom
Communication dans un congrès
hal-01135198v1
|
||
|
|
Optimal transport-based dictionary learning and its application to Euclid-like Point Spread Function representationWavelets and Sparsity XVII, Aug 2017, San Diego, United States. pp.103940H, ⟨10.1117/12.2270641⟩
Communication dans un congrès
hal-01635342v1
|
||
|
|
A Smoothed Dual Approach for Variational Wasserstein ProblemsSIAM Journal on Imaging Sciences, 2015
Article dans une revue
hal-01188954v1
|
||
|
|
Spatio-Temporal Alignments: Optimal transport through space and time2019
Pré-publication, Document de travail
hal-02309340v2
|
||
Computational Optimal TransportFoundations and Trends in Machine Learning, 2018, 11 (5-6), pp.355-206. ⟨10.1561/2200000073⟩
Article dans une revue
hal-02411770v1
|
|||
|
|
Etude de noyaux de semigroupe pour objets structurés dans le cadre de l'apprentissage statistiqueMathematics [math]. École Nationale Supérieure des Mines de Paris, 2005. English. ⟨NNT : ⟩
Thèse
pastel-00001823v1
|
||
|
|
Iterative Bregman Projections for Regularized Transportation ProblemsSIAM Journal on Scientific Computing, 2015, 2 (37), pp.A1111-A1138. ⟨10.1137/141000439⟩
Article dans une revue
hal-01096124v1
|
||
|
|
Wasserstein Dictionary Learning: Optimal Transport-based unsupervised non-linear dictionary learningSIAM Journal on Imaging Sciences, 2018, 11 (1), pp.643-678. ⟨10.1137/17M1140431⟩
Article dans une revue
hal-01717943v2
|
||
|
|
Ground Metric Learning on GraphsJournal of Mathematical Imaging and Vision, 2021, 63 (1), pp.89-107. ⟨10.1007/s10851-020-00996-z⟩
Article dans une revue
hal-02989081v1
|
||
|
|
Convolutional wasserstein distancesACM Transactions on Graphics, 2015, 34 (4), pp.66:1-66:11. ⟨10.1145/2766963⟩
Article dans une revue
hal-01188953v1
|
||
|
|
Gromov-Wasserstein Averaging of Kernel and Distance MatricesICML 2016, Jun 2016, New-York, United States
Communication dans un congrès
hal-01322992v1
|
||
|
|
Stochastic Optimization for Large-scale Optimal TransportNIPS 2016 - Thirtieth Annual Conference on Neural Information Processing System, Dec 2016, Barcelona, Spain
Communication dans un congrès
hal-01321664v2
|
||
|
|
Wasserstein Discriminant AnalysisMachine Learning, 2018, 107 (12), pp.1923-1945. ⟨10.1007/s10994-018-5717-1⟩
Article dans une revue
hal-01377528v1
|
||
|
|
Sample Complexity of Sinkhorn divergencesAISTATS'19 - 22nd International Conference on Artificial Intelligence and Statistics, Apr 2019, Okinawa, Japan
Communication dans un congrès
hal-02411822v1
|
||
|
|
Log-PCA versus Geodesic PCA of histograms in the Wasserstein spaceSIAM Journal on Scientific Computing, 2018, 40 (2), pp.B429-B456
Article dans une revue
hal-01581699v2
|
||
|
|
Regularity as Regularization: Smooth and Strongly Convex Brenier Potentials in Optimal TransportAISTATS 2020 - 23rd International Conference on Artificial Intelligence and Statistics, Jun 2020, Palermo / Virtual, Italy
Communication dans un congrès
hal-02340371v1
|
||
The context-tree kernel for strings.Neural Networks, 2005, 18 (8), pp.1111-23. ⟨10.1016/j.neunet.2005.07.010⟩
Article dans une revue
istex
hal-00433583v1
|
|||
|
|
Multiresolution Kernels2005
Pré-publication, Document de travail
hal-00007489v2
|
||
|
|
Mean Reversion with a Variance ThresholdInternational Conference on Machine Learning, Jun 2013, United States. pp.271-279
Communication dans un congrès
hal-00939566v1
|
||
Large Scale computation of Means and Clusters for Persistence Diagrams using Optimal TransportNIPS, 2018, Montreal, Canada
Communication dans un congrès
hal-01966674v1
|
|||
|
|
Wasserstein Barycentric Coordinates: Histogram Regression Using Optimal TransportACM Transactions on Graphics, 2016, 35 (4), pp.71:1--71:10. ⟨10.1145/2897824.2925918⟩
Article dans une revue
hal-01303148v1
|
||
|
|
Debiased Sinkhorn barycentersICML 2020 - 37th International Conference on Machine Learning, Jul 2020, Vienna / Virtuel, Austria
Communication dans un congrès
hal-03063875v1
|
||
|
|
Sliced Wasserstein Kernel for Persistence DiagramsInternational Conference on Machine Learning, Aug 2017, Sydney, Australia
Communication dans un congrès
hal-01633105v1
|