131 citations · 319 across the 16 of their papers we have counts for
16 papers
Textbooks Are All You Need
Suriya Gunasekar, Yi Zhang, Jyoti Aneja +16
We introduce phi-1, a new large language model for code, with significantly smaller size than competing models: phi-1 is a Transformer-based model with 1.3B parameters, trained for…
Enhancing Hyper-To-Real Space Projections Through Euclidean Norm Meta-Heuristic Optimization
Luiz C. F. Ribeiro, Mateus Roder, Gustavo H. de Rosa +2
The continuous computational power growth in the last decades has made solving several optimization problems significant to humankind a tractable task; however, tackling some of th…
A survey on text generation using generative adversarial networks
Gustavo Henrique de Rosa, João Paulo Papa
This work presents a thorough review concerning recent studies and text generation advancements using Generative Adversarial Networks. The usage of adversarial learning for text ge…
Improving Pre-Trained Weights Through Meta-Heuristics Fine-Tuning
Gustavo H. de Rosa, Mateus Roder, João Paulo Papa +1
Machine Learning algorithms have been extensively researched throughout the last decade, leading to unprecedented advances in a broad range of applications, such as image classific…
From Actions to Events: A Transfer Learning Approach Using Improved Deep Belief Networks
Mateus Roder, Jurandy Almeida, Gustavo H. de Rosa +3
In the last decade, exponential data growth supplied machine learning-based algorithms' capacity and enabled their usage in daily-life activities. Additionally, such an improvement…
Robust deep learning for eye fundus images: Bridging real and synthetic data for enhancing generalization
Guilherme C. Oliveira, Gustavo H. Rosa, Daniel C. G. Pedronette +4
Deep learning applications for assessing medical images are limited because the datasets are often small and imbalanced. The use of synthetic data has been proposed in the literatu…
LiteTransformerSearch: Training-free Neural Architecture Search for Efficient Language Models
Mojan Javaheripi, Gustavo H. de Rosa, Subhabrata Mukherjee +6
The Transformer architecture is ubiquitously used as the building block of large-scale autoregressive language models. However, finding architectures with the optimal trade-off bet…
Comparative Study Between Distance Measures On Supervised Optimum-Path Forest Classification
Gustavo Henrique de Rosa, Mateus Roder, João Paulo Papa
Machine Learning has attracted considerable attention throughout the past decade due to its potential to solve far-reaching tasks, such as image classification, object recognition,…
Speeding Up OPFython with Numba
Gustavo H. de Rosa, João Paulo Papa
A graph-inspired classifier, known as Optimum-Path Forest (OPF), has proven to be a state-of-the-art algorithm comparable to Logistic Regressors, Support Vector Machines in a wide…
Energy-based Dropout in Restricted Boltzmann Machines: Why not go random
Mateus Roder, Gustavo H. de Rosa, Victor Hugo C. de Albuquerque +2
Deep learning architectures have been widely fostered throughout the last years, being used in a wide range of applications, such as object recognition, image reconstruction, and s…
A Nature-Inspired Feature Selection Approach based on Hypercomplex Information
Gustavo H. de Rosa, João Paulo Papa, Xin-She Yang
Feature selection for a given model can be transformed into an optimization task. The essential idea behind it is to find the most suitable subset of features according to some cri…
Fast Ensemble Learning Using Adversarially-Generated Restricted Boltzmann Machines
Gustavo H. de Rosa, Mateus Roder, João P. Papa
Machine Learning has been applied in a wide range of tasks throughout the last years, ranging from image classification to autonomous driving and natural language processing. Restr…
Learnergy: Energy-based Machine Learners
Mateus Roder, Gustavo Henrique de Rosa, João Paulo Papa
Throughout the last years, machine learning techniques have been broadly encouraged in the context of deep learning architectures. An exciting algorithm denoted as Restricted Boltz…
OPFython: A Python-Inspired Optimum-Path Forest Classifier
Gustavo Henrique de Rosa, João Paulo Papa, Alexandre Xavier Falcão
Machine learning techniques have been paramount throughout the last years, being applied in a wide range of tasks, such as classification, object recognition, person identification…
Opytimizer: A Nature-Inspired Python Optimizer
Gustavo H. de Rosa, Douglas Rodrigues, João P. Papa
Optimization aims at selecting a feasible set of parameters in an attempt to solve a particular problem, being applied in a wide range of applications, such as operations research,…
LibOPT: An Open-Source Platform for Fast Prototyping Soft Optimization Techniques
Joao Paulo Papa, Gustavo Henrique Rosa, Douglas Rodrigues +1
Optimization techniques play an important role in several scientific and real-world applications, thus becoming of great interest for the community. As a consequence, a number of o…