6 citations · 11 across the 6 of their papers we have counts for
6 papers
Single-Solution Hypervolume Maximization and its use for Improving Generalization of Neural Networks
Conrado S. Miranda, Fernando J. Von Zuben
This paper introduces the hypervolume maximization with a single solution as an alternative to the mean loss minimization. The relationship between the two problems is proved throu…
Reducing the Training Time of Neural Networks by Partitioning
Conrado S. Miranda, Fernando J. Von Zuben
This paper presents a new method for pre-training neural networks that can decrease the total training time for a neural network while maintaining the final performance, which moti…
Multi-Objective Optimization for Self-Adjusting Weighted Gradient in Machine Learning Tasks
Conrado Silva Miranda, Fernando José Von Zuben
Much of the focus in machine learning research is placed in creating new architectures and optimization methods, but the overall loss function is seldom questioned. This paper inte…
Hybrid Algorithm for Multi-Objective Optimization by Greedy Hypervolume Maximization
Conrado Silva Miranda, Fernando José Von Zuben
This paper introduces a high-performance hybrid algorithm, called Hybrid Hypervolume Maximization Algorithm (H2MA), for multi-objective optimization that alternates between explori…
Efficient Simultaneous Calibration of a Magnetometer and an Accelerometer
Conrado Silva Miranda, Janito Vaqueiro Ferreira
This paper describes a calibration algorithm to simultaneously calibrate a magnetometer and an accelerometer without any information besides the sensors readings. Using a linear se…
Asymmetric Distributions from Constrained Mixtures
Conrado S. Miranda, Fernando J. Von Zuben
This paper introduces constrained mixtures for continuous distributions, characterized by a mixture of distributions where each distribution has a shape similar to the base distrib…