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Diffusion LMS was originally conceived for online distributed parameter estimation in single-task environments where agents pursue a common objective. However, estimating distinct but correlated objects (multitask problems) is useful in many applications. ...
We consider the problem of designing controllers for nonholonomic mobile robots converging to the source (minimum) of a field. In addition to the mobility constraints posed by the nonholonomic dynamics, we assume that the field is completely unknown to the ...
We consider the classical k-means clustering problem in the setting of bi-criteria approximation, in which an algorithm is allowed to output beta*k > k clusters, and must produce a clustering with cost at most alpha times the to the cost of the optimal set ...
Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik2016
We propose a novel algorithm for automatic text line extraction on color and grayscale manuscript pages without prior binarization.
Our algorithm is based on seam carving to compute separating seams between text lines.
Seam carving is likely to produce ...
We consider the transfer learning scenario, where the learner does not have access to the source domain directly, but rather operates on the basis of hypotheses induced from it - the Hypothesis Transfer Learning (HTL) problem. Particularly, we conduct a th ...
Diffusion LMS is an efficient strategy for solving distributed optimization problems with cooperating agents. In some applications, the optimum parameter vectors may not be the same for all agents. Moreover, agents usually exchange information through nois ...
The level set method is a popular technique for tracking moving interfaces in several disciplines including computer vision and fluid dynamics. However, despite its high flexibility, the original level set method is limited by two important numerical issue ...
Institute of Electrical and Electronics Engineers2012
In this work, we consider distributed adaptive learning over multitask mean-square-error (MSE) networks where each agent is interested in estimating its own parameter vector, also called task, and where the tasks at neighboring agents are related according ...
The multitask diffusion LMS algorithm is an efficient strategy to address distributed estimation problems that are multitask-oriented in the sense that the optimum parameter vector may not be the same for every cluster of nodes. In this work, we explore th ...
Stochastic modeling is a challenging task for low-cost sensors whose errors can have complex spectral structures. This makes the tuning process of the INS/GNSS Kalman filter often sensitive and difficult. For example, first-order Gauss–Markov processes are ...
