Titlebook: Machine Learning and Knowledge Discovery in Databases; European Conference, José Luis Balcázar,Francesco Bonchi,Michèle Sebag Conference pr

HERE

虚度

Vector Field Learning via Spectral Filteringh faster than Tikhonov regularization and attain the same prediction performances. Finite sample bounds for the different filters can be derived in a common framework and highlight different theoretical properties of the methods. The theory of vector valued reproducing kernel Hilbert space is a key tool in our study.

nominal

Promotion

Sleep-Paralysis

vasospasm

自恋

Porting Decision Tree Algorithms to Multicore Using FastFlowat makes them suitable to be parallelised. This paper presents an approach for . porting of an implementation of the C4.5 algorithm on multicores. The parallel porting requires minimal changes to the original sequential code, and it is able to exploit up to 7× speedup on an Intel dual-quad core machine.

LAITY

Leveraging Bagging for Evolving Data Streamsontext of evolving data streams. In this paper, we propose a new variant of bagging, called .. This method combines the simplicity of bagging with adding more randomization to the input, and output of the classifiers. We test our method by performing an evaluation study on synthetic and real-world datasets comprising up to ten million examples.

脆弱吧

Coniunge et Impera: Multiple-Graph Mining for Query-Log Analysisut by applying simple but efficient graph-mining techniques. We show that our approach achieves very good performance for two different applications, which are classifying query transitions and recognizing spam queries.

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