Adaptive indexing is characterized by the partial creation and refinement of the index as side effects of query execution. Dynamic or shifting workloads may benefit from prelimi...
Stratos Idreos, Stefan Manegold, Harumi A. Kuno, G...
We give a review of various aspects of boosting, clarifying the issues through a few simple results, and relate our work and that of others to the minimax paradigm of statistics. ...
In this paper we propose an Rprop modification that builds on a mathematical framework for the convergence analysis to equip Rprop with a learning rates adaptation strategy that en...
Aristoklis D. Anastasiadis, George D. Magoulas, Mi...
The success of tensor-based subspace learning depends heavily on reducing correlations along the column vectors of the mode-k flattened matrix. In this work, we study the problem ...
Shuicheng Yan, Dong Xu, Stephen Lin, Thomas S. Hua...
An efficient and general multiple kernel learning (MKL) algorithm has been recently proposed by Sonnenburg et al. (2006). This approach has opened new perspectives since it makes ...