Lanczos-hybrid regularization methods have been proposed as effective approaches for solving largescale ill-posed inverse problems. Lanczos methods restrict the solution to lie in a Krylov subspace, but they are hindered by semi-convergence behavior, in that the quality of the solution first increases and then decreases. Hybrid methods apply a standard regularization technique, such as Tikhonov...

We propose a stochastic variance-reduced cubic regularized Newton method for non-convex optimization. At the core of our algorithm is a novel semi-stochastic gradient along with a semi-stochastic Hessian, which are specifically designed for cubic regularization method. We show that our algorithm is guaranteed to converge to an ( , √ )-approximately local minimum within Õ(n/ ) second-order oracl...

In semi-supervised learning (SSL), we learn a predictive model from a collection of labeled data and a typically much larger collection of unlabeled data. These lecture notes present a framework called multi-view point cloud regularization (MVPCR) [5], which unifies and generalizes several semi-supervised kernel methods that are based on data-dependent regularization in reproducing kernel Hilbe...

In semi-supervised learning (SSL), we learn a predictive model from a collection of labeled data and a typically much larger collection of unlabeled data. These lecture notes present a framework called multi-view point cloud regularization (MVPCR) [5], which unifies and generalizes several semi-supervised kernel methods that are based on data-dependent regularization in reproducing kernel Hilbe...

The idea of local learning, i.e., classifying a particular example based on its neighbors, has been successfully applied to many semi-supervised and clustering problems recently. However, the local learning methods developed so far are all devised for single-view problems. In fact, in many real-world applications, examples are represented by multiple sets of features. In this paper, we extend t...

we present a mathematical model describing the motion of two elastic rods in contact. The model allows for large displacements and is essentially based on Cosserat’s modelling of rods. Using a penalty technique, we prove existence of a static solution in the case of a unique rod. The contact modelling involves unilateral constraints on the central lines of the rods. Existence is also proved for...

Non-stationarity is ubiquitous in human behavior and addressing it the contextual bandits challenging. Several works have addressed problem by investigating semi-parametric warned that ignoring non-stationarity could harm performances. Another prevalent social interaction which has become available a form of network or graph structure. As result, graph-based received much attention. In this pap...