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The goal of transductive learning is to find a way to recover the labels of lots of data with only a few known samples. In this work, we will work on graphs for two reasons. First, it’s possible to construct a graph from a given dataset with features. The ...
In order to achieve reliable information about deterioration, it is important to differentiate between changes in structural behaviour due to service loading (temperature, wind and traffic) and changes resulting from damage when interpreting measurement da ...
We consider regression problems with piecewise affine maps. In particular, we focus on the sub-problem of classifying the datapoints, i.e. correctly attributing a datapoint to the affine submodel that most likely generated it. Then, we analyze the regressi ...
This letter provides a unified mean-square performance analysis of the class of data reusing adaptive algorithms. The derivation relies on energy conservation arguments, and it does not restrict the regression data to being Gaussian. Simulation results sho ...
This article provides an overview of an energy-based approach to the study of the steady-state and transient performances of adaptive filters. The analysis employs energy-conservation arguments and is based on studying the energy flow through each iteratio ...
The paper develops a unified approach to the transient analysis of adaptive filters with error nonlinearities. In addition to deriving earlier results in a unified manner, the approach also leads to new performance results without restricting the regressio ...
To restore walking after transfemoral amputation, various actuated exoprostheses have been developed, which control the knee torque actively or via variable damping. In both cases, an important issue is to find the appropriate control that enables user-dom ...
Multimodal biometric authentication (BA) has shown perennial successes both in research and applications. This paper casts a light on why BA systems can be improved by fusing opinions of different experts, principally due to diversity of biometric modaliti ...
FMRI time course processing is traditionally performed using linear regression followed by statistical hypothesis testing. While this analysis method is robust against noise, it relies strongly on the signal model. In this paper, we propose a non-parametri ...
FMRI time course processing is traditionally performed using linear regression followed by statistical hypothesis testing. While this analysis method is robust against noise, it relies strongly on the signal model. In this paper, we propose a non-parametri ...
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