— This paper addresses the problem of acquiring a hierarchically structured robotic skill in a nonstationary environment. This is achieved through a combination of learning primi...
One of the objectives of this paper is to verify whether it is possible to extract meaningful related tags from a limited set of tagged resources and from resources tagged by only ...
We propose CCRank, the first parallel algorithm for learning to rank, targeting simultaneous improvement in learning accuracy and efficiency. CCRank is based on cooperative coev...
Shuaiqiang Wang, Byron J. Gao, Ke Wang, Hady Wiraw...
We present a novel approach to learn a kernelbased regression function. It is based on the use of conical combinations of data-based parameterized kernels and on a new stochastic ...
Pierre Machart, Thomas Peel, Liva Ralaivola, Sandr...
The goal of this paper is to investigate the impact of dictionary choosing for a total variation dictionary model. After theoretical analysis, we present the experiments in which ...