[PDF] Top 20 Metric learning for structured data

... ween data structure and features. For example, when processing a database of commodity classification information, each of the data is composed of independent indicators of the commodity, and the ... Voir le document complet

... of metric learning approaches are dedicated to be ap- plied on data described by feature vectors, with some no- table exceptions such as times series, trees or ...a metric learning al- ... Voir le document complet

... the data analysis perspective, this can be formalized as a multiclass classification ...This learning task presents several challenging ...machine learning methods were indeed recently proposed ... Voir le document complet

... In (Geurts & Wehenkel, 2005), we have applied the segment and combine method on 10 benchmark time- series problems and obtained results competitive with state-of-the-art algorithms from the literature without any ... Voir le document complet

... imaging data for AD diagnosis. We started with the idea that learning AD diagnosis from imaging data already provides good ...imaging data could be modulated, depending on each ... Voir le document complet

... Figure 6.2 Left: Overlayed back valley curves (preoperative (blue) and postoperative (red)) on a patient surface mesh. Right: Displacement vector field along the back valley curve from preoperative to postoperative ... Voir le document complet

... labels for these datasets, following the protocols of previous works ( Du et ...filter learning of GCKN-subtree does not ...allowing for faster classification at test ... Voir le document complet

... the data sets, and that the ground truth annotations do not always contain all relevant tags ...‘water’ for the bottom left image), and sometimes contain tags for which one can argue whether they are ... Voir le document complet

... accounts for subject-to-subject differences, one of its major limitations is that it does not model spatial variability across ...smoothed data: isotropic FWHM of 6mm, a necessary preprocessing step ... Voir le document complet

... joint learning from partially structured graph databases, where we want to learn at the same time the ER schema and the probabilistic ...solution for this ...structure learning algorithm could ... Voir le document complet

... with metric learning by Simonyan et al. [2], novel regularization for similarity met- ric learning by Cao et ...multiple metric learning by Cui et al. [31], deep learning ... Voir le document complet

... The usefulness of the proposed approach is evaluated on several datasets with up to 100,000 features, some of which have a large proportion of irrelevant features. To the best of our knowledge, this is the first time ... Voir le document complet

... the data analysis perspective, this can be formalized as a multiclass classification ...This learning task presents several challenging ...machine learning methods were indeed recently proposed ... Voir le document complet

... complex data distribu- tions is to incorporate fewer assumptions, but rather parameterize the generative model with a neural network that can learn a suitable generative process from many different ... Voir le document complet

... a data-driven system to learn to predict fault structures automatically from a set of training data consisting of (seismic traces, faults) ...difficult for people to directly interpret the raw ... Voir le document complet

... kernel for the reconstruction of two biological networks: the metabolic network and the co-complex protein ...network. For each network, we cast the problem of network reconstruction as a binary ... Voir le document complet

... Table 5: Accuracy of KNN with different metrics learning algorithm and their running time in seconds. datasets as in the previous experiment, but we make ξ of the ξ-additive varies from 1 to min(10, m). A value of ... Voir le document complet

... the learning and inference complexity lin- ear in the number of classes become ...training data per class becomes very ...proaches, metric learning becomes a very appealing tech- nique in this ... Voir le document complet

... range for drugs), since the aim was to evaluate if statistical learning was possible on drug-like ...suitable for the use of 3D ...GLIDA data bank, and giving 4051 interactions with the human ... Voir le document complet

... 1 Brainomics Team, Neurospin, CEA Saclay, 91190 Gif sur Yvette – France. † These authors contributed equally to this work. Abstract A very active field of research in Bioinformatics is to integrate structure in Machine ... Voir le document complet