4 papers
A stochastic approach to handle knapsack problems in the creation of ensembles
Andras Hajdu, Gyorgy Terdik, Attila Tiba +1
Ensemble-based methods are highly popular approaches that increase the accuracy of a decision by aggregating the opinions of individual voters. The common point is to maximize accu…
Efficient Learning of Model Weights via Changing Features During Training
Marcell Beregi-Kovács, Ágnes Baran, András Hajdu
In this paper, we propose a machine learning model, which dynamically changes the features during training. Our main motivation is to update the model in a small content during the…
Optimizing Majority Voting Based Systems Under a Resource Constraint for Multiclass Problems
Attila Tiba, Andras Hajdu, Gyorgy Terdik +1
Ensemble-based approaches are very effective in various fields in raising the accuracy of its individual members, when some voting rule is applied for aggregating the individual de…
Finding well approximating lattices for a finite set of points
A. Hajdu, L. Hajdu, R. Tijdeman
In this paper we address the problem of finding well approximating lattices for a given finite set of points in . More precisely, we search for $ǒ,\v{d_1}, \dots…