1 citations · 2 across the 9 of their papers we have counts for
4 papers · 1 filter
Online variants of the cross-entropy method
Istvan Szita, Andras Lorincz
The cross-entropy method is a simple but efficient method for global optimization. In this paper we provide two online variants of the basic CEM, together with a proof of convergen…
Selection in Scale-Free Small World
Zs. Palotai, Cs. Farkas, A. Lorincz
In this paper we compare the performance characteristics of our selection based learning algorithm for Web crawlers with the characteristics of the reinforcement learning algorithm…
L1 regularization is better than L2 for learning and predicting chaotic systems
Z. Szabo, A. Lorincz
Emergent behaviors are in the focus of recent research interest. It is then of considerable importance to investigate what optimizations suit the learning and prediction of chaotic…
Kalman filter control in the reinforcement learning framework
Istvan Szita, Andras Lorincz
There is a growing interest in using Kalman-filter models in brain modelling. In turn, it is of considerable importance to make Kalman-filters amenable for reinforcement learning.…