In this report we show some simple properties of SVM for regression. In particular we show that for close to zero, minimizing the norm of w is equivalent to maximizing the distance between the optimal approximating hyperplane solution of SVMR and the closest points in the data set. So, in this case, there exists a complete analogy between SVM for regression and classiication, and the-tube plays...

In this paper, we study the set of homogeneous geodesics of a leftinvariant Finsler metric on Lie groups. We first give a simple criterion that characterizes geodesic vectors. As an application, we study some geometric properties of bi-invariant Finsler metrics on Lie groups. In particular a necessary and sufficient condition that left-invariant Randers metrics are of Berwald type is given. Fin...

Learning how to extract texture features from noncontrolled environments characterized by distorted images is a still-open task. By using a new rotation-invariant and scale-invariant image descriptor based on steerable pyramid decomposition, and a novel multiclass recognition method based on optimum-path forest, a new texture recognition system is proposed. By combining the discriminating power...

We discuss the asymptotic behaviour of solutions for the nonlocal quasilinear hyperbolic problem of Kirchhoff Type [ u_{tt}-phi (x)||nabla u(t)||^{2}Delta u+delta u_{t}=|u|^{a}u,, x in mathbb{R}^{N} ,,tgeq 0;,]with initial conditions $u(x,0) = u_0 (x)$ and $u_t(x,0) = u_1 (x)$, in the case where $N geq 3, ; delta geq 0$ and $(phi (x))^{-1} =g (x)$  is a positive function lying in $L^{N/2}(mathb...

Previous work [Bowman et al., 2016] has shown that variational autoencoders (VAEs) can create distributed representations of natural language that capture different linguistic levels such as syntax, semantics, and style in a holistic manner. I investigate to what extent VAEs, when trained on different languages, result in comparable representations. To this end, I train VAEs for English and Fre...

This paper investigates a new yet challenging problem called Reverse k-Maximum Inner Product Search (RkMIPS). Given query (item) vector, set of item vectors, and user the RkMIPS aims to find vectors whose inner products with vector are one k largest among vectors. We propose first subquadratic-time algorithm, i.e., Shifting-aware Asymmetric Hashing (SAH), tackle problem. To speed up Maximum (MI...