Irregular (quasi)varieties of groupoids are (quasi)varieties that do not contain semilattices. The regularization of a (strongly) irregular variety V of groupoids is the smallest variety containing V and the variety S of semilattices. Its quasiregularization is the smallest quasivariety containing V and S. In an earlier paper the authors described the lattice of quasivarieties of cancellative c...

This paper introduces the use of vector fields to design, optimize, and implement reactive schedules for safe cooperative robot patterns on planar graphs. We consider automated guided vehicles (AGVs) operating upon a predefined network of pathways. In contrast to the case of locally Euclidean configuration spaces, regularization of collisions is no longer a local procedure, and issues concernin...

It is well known that the generalization capability is one of the most important criterions to develop and evaluate a classifier for a given pattern classification problem. The localized generalization error model (RSM) [2, 12] recently proposed by Ng et al. provides a more intuitive look at the generalization error. Although RSM gives a brand-new method to promote the generalization performanc...

In many areas of science and engineering, the problem arises how to discover low dimensional representations of high dimensional data. Recently, a number of researchers have converged on common solutions to this problem using methods from convex optimization. In particular, many results have been obtained by constructing semidefinite programs (SDPs) with low rank solutions. While the rank of ma...

Anchor texts are useful complementary description for target pages, widely applied to improve search relevance. The benefits come from the additional information introduced into document representation and the intelligent ways of estimating their relative importance. Previous work on anchor importance estimation treated anchor text independently without considering its context. As a result, the...

Light field cameras can capture the 3D information in a scene with a single shot. This special feature makes light field cameras very appealing for a variety of applications: from the popular post-capture refocus, to depth estimation and imagebased rendering. However, light field cameras suffer by design from strong limitations in their spatial resolution, which should therefore be augmented by...

The advent of high-throughput DNA sequencing methods has led to an explosion in the availability of genome-wide data and a corresponding opportunity to use computational methods to derive insights into cellular function. A predominant form of statistical model used for genomic data has been temporal, such as the hidden Markov model (HMM) (Rabiner, 1989) or dynamic Bayesian network (DBN) (Dean a...

Considering the increasing availability of structured machine processable knowledge in the context of the Semantic Web, only relying on purely deductive inference may be limiting. This work proposes a new method for similaritybased class-membership prediction in Description Logic knowledge bases. The underlying idea is based on the concept of propagating class-membership information among simil...

The data in many real-world problems can be thought of as a graph, such as the web, co-author networks, and biological networks. We propose a general regularization framework on graphs, which is applicable to the classification, ranking, and link prediction problems. We also show that the method can be explained as lazy random walks. We evaluate the method on a number of experiments.

We address in this paper the question of how the knowledge of the marginal distribution P (x) can be incorporated in a learning algorithm. We suggest three theoretical methods for taking into account this distribution for regularization and provide links to existing graph-based semi-supervised learning algorithms. We also propose practical implementations.