Titlebook: Machine Learning and Knowledge Discovery in Databases; European Conference, Annalisa Appice,Pedro Pereira Rodrigues,Alípio Jor Conference p

abduction

放逐某人

Fast Label Embeddings via Randomized Linear Algebrasettings. The result is a randomized algorithm whose running time is exponentially faster than naive algorithms. We demonstrate our techniques on two large-scale public datasets, from the Large Scale Hierarchical Text Challenge and the Open Directory Project, where we obtain state of the art results.

perjury

Regression with Linear Factored FunctionsWe derive a regularized greedy optimization scheme, that learns factored basis functions during training. The novel regression algorithm performs competitively to . on benchmark tasks, and the learned LFF functions are with 4-9 factored basis functions on average very compact.

Apoptosis

Ridge Regression, Hubness, and Zero-Shot Learningprove that the proposed approach indeed reduces hubness. This was verified empirically on the tasks of bilingual lexicon extraction and image labeling: hubness was reduced with both of these tasks and the accuracy was improved accordingly.

懶惰人民

Erythropoietin

安撫

富足女人

Customary

ConDist: A Context-Driven Categorical Distance Measureal distance measures and evaluate on different data sets from the UCI machine-learning repository. The experiments show that our distance measure is recommendable, since it achieves similar or better results in a more robust way than previous approaches.

gangrene

Conference proceedings 2015overy in Databases, ECML PKDD 2015, held in Porto, Portugal, in September 2015. .The 131 papers presented in these proceedings were carefully reviewed and selected from a total of 483 submissions. These include 89 research papers, 11 industrial papers, 14 nectar papers, and 17 demo papers. They were