We reformulate a recently introduced interpolation-based unique decoding algorithm of algebraic geometry codes using the theory of Gröbner bases of modules on the coordinate ring of the base curve. With the same decoding performance, the new algorithm has a more conceptual description that lets us better understand the majority voting procedure central in the interpolation-based unique decoding.

Voting on the outputs of redundant modules with real number results (i.e., where correctly functioning redundant systems may arrive at slightly different yet correct outputs for identical inputs) is not straightforward. Such cases need inexact voting in which some discrepancies between the outputs of redundant modules are allowed. Documented inexact voters use a fixed threshold value that may c...

The POSSIBLE-WINNER problem asks, given an election where the voters’ preferences over the set of candidates is partially specified, whether a distinguished candidate can become a winner. In this work, we consider the computational complexity of POSSIBLE-WINNER under the assumption that the voter preferences are partitioned. That is, we assume that every voter provides a complete order over set...

This article proposes a method improving Kong et al. algorithm called Locally Adaptive Soft-Voting (LASV) algorithm described in ”General road detection from a single image”. This algorithm aims to detect and segment road in structured and unstructured environments. Evaluation of our method over different images datasets shows that it is speeded up by up to 32 times and precision is improved by...

This paper is concerned with the problem of dynamic taskassignment among multiple mobile agents. We study and experimentally compare two approaches for achieving an agreement on how the tasks are to be assigned: negotiation through auctions and aggregation of preferences through voting. For the second approach, we formalize the task assignment problem as a voting problem and present the corresp...

An incremental learning algorithm, Learn—, is introduced, for learning additional information from new data, even when new data include examples of previously unseen classes. Learn++ takes advantage of synergistic generalization performance of an ensemble of simple classifiers, each trained with a strategically chosen subset of the training database. As new data become available, new classifier...

Cardiac catheter ablation is a minimally invasive medical procedure to treat patients with heart rhythm disorders. It is useful to know the positions of the catheters and electrodes during the intervention, e.g. for the automatization of cardiac mapping. Our goal is therefore to develop a robust image analysis method that can detect the catheters in X-ray fluoroscopy images. Our method uses ste...

We consider the problem of identifying and estimating non-zero parameters in the Markov model for binary variables. We approximate the full likelihood by a pseudolikelihood function and propose a joint `1-penalized logistic regression method, which imposes overall sparsity on the parameters. We show that the proposed method leads to consistent parameter estimation and model selection under high...