40 citations · 80 across the 7 of their papers we have counts for
9 papers
An Extension of the Non-Inferior Set Estimation Algorithm for Many Objectives
Marcos M. Raimundo, Paulo A. V. Ferreira, Fernando J. Von Zuben
This work proposes a novel multi-objective optimization approach that globally finds a representative non-inferior set of solutions, also known as Pareto-optimal solutions, by auto…
Online Multi-Task Learning with Recursive Least Squares and Recursive Kernel Methods
Gabriel R. Lencione, Fernando J. Von Zuben
This paper introduces two novel approaches for Online Multi-Task Learning (MTL) Regression Problems. We employ a high performance graph-based MTL formulation and develop two altern…
An Extension of the Non-Inferior Set Estimation Algorithm for Many Objectives
Marcos M. Raimundo, Fernando J. Von Zuben
This work proposes a novel multi-objective optimization approach that globally finds a representative non-inferior set of solutions, also known as Pareto-optimal solutions, by auto…
Effects of Social Ties in Knowledge Diffusion: case study on PLOS ONE
Felipe Eltermann, Alan Godoy, Fernando J. Von Zuben
In order to capture the effects of social ties in knowledge diffusion, this paper examines the publication network that emerges from the collaboration of researchers, using citatio…
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…
Multi-task Sparse Structure Learning
Andre R. Goncalves, Puja Das, Soumyadeep Chatterjee +3
Multi-task learning (MTL) aims to improve generalization performance by learning multiple related tasks simultaneously. While sometimes the underlying task relationship structure i…
Enumerating all maximal biclusters in numerical datasets
Rosana Veroneze, Arindam Banerjee, Fernando J. Von Zuben
Biclustering has proved to be a powerful data analysis technique due to its wide success in various application domains. However, the existing literature presents efficient solutio…