Our two algorithms, SAOLA and group-SAOLA, are scalable on datasets of extremely high dimensionality and have superior performance over the state-of-the-art ...
Nov 30, 2015 · We present SAOLA, a Scalable and Accurate OnLine Approach for feature selection in this paper. With a theoretical analysis on bounds of the ...
We present SAOLA, a Scalable and Accurate OnLine Approach for feature selection in this paper. With a theoretical analysis on bounds of the pairwise ...
Secondly, feature selection has to be highly scalable, preferably in an online manner such that each feature can be processed in a sequential scan. In this ...
In this paper, we tackle the challenges in online feature selection from extremely high dimensional data, and develop. SAOLA, a Scalable and Accurate OnLine ...
—With this theoretical analysis, we develop SAOLA, a Scalable and Accurate OnLine. Approach for feature selection. The SAOLA algorithm employs novel online ...
Secondly, feature selection has to be highly scalable, preferably in an online manner such that each feature can be processed in a sequential scan. In this ...
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We present SAOLA, a Scalable and Accurate OnLine Approach for feature selection in this paper. With a theoretical analysis on bounds of the pairwise ...
An empirical study shows that SAOLA is scalable on data sets of extremely high dimensionality, and has superior performance over the state-of-the-art ...
We present SAOLA, a Scalable and Accurate OnLine Approach for feature selection in this paper. With a theoretical analysis on bounds of the pairwise ...