Abstract-- This paper introduces a deterministic approximation algorithm with error guarantees for computing the probability of propositional formulas over discrete random variable...
— Reinforcement learning (RL) is a learning control paradigm that provides well-understood algorithms with good convergence and consistency properties. Unfortunately, these algor...
Lucian Busoniu, Damien Ernst, Bart De Schutter, Ro...
Determining node positions is essential for many next-generation network functionalities. Previous localization algorithms lack correctness guarantees or require network density h...
David Kiyoshi Goldenberg, Pascal Bihler, Yang Rich...
In this paper the problem of fault-tolerant message routing in two-dimensional meshes, with each inner node having 4 neighbors, is investigated. It is assumed that some nodes/links...
Abstract. We focus on two recently proposed algorithms in the family of “boosting”-based learners for automated text classification, AdaBoost.MH and AdaBoost.MHKR . While the ...
Pio Nardiello, Fabrizio Sebastiani, Alessandro Spe...