Danilo Vasconcellos Vargas

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KYUSHU UNIVERSITY

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Perceptual Deep Neural Networks: Adversarial Robustness through Input Recreation

Adversarial examples have shown that albeit highly accurate, models lear...
09/02/2020 ∙ by Danilo Vasconcellos Vargas, et al. ∙ 11 ∙ share

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Continual General Chunking Problem and SyncMap

Humans possess an inherent ability to chunk sequences into their constit...
06/14/2020 ∙ by Danilo Vasconcellos Vargas, et al. ∙ 0 ∙ share

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Evolving Robust Neural Architectures to Defend from Adversarial Attacks

Deep neural networks were shown to misclassify slightly modified input i...
06/27/2019 ∙ by Danilo Vasconcellos Vargas, et al. ∙ 8 ∙ share

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Uncovering Why Deep Neural Networks Lack Robustness: Representation Metrics that Link to Adversarial Attacks

Neural networks have been shown vulnerable to adversarial samples. Sligh...
06/15/2019 ∙ by Danilo Vasconcellos Vargas, et al. ∙ 0 ∙ share

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Model Agnostic Dual Quality Assessment for Adversarial Machine Learning and an Analysis of Current Neural Networks and Defenses

In adversarial machine learning, there are a huge number of attacks of v...
06/14/2019 ∙ by Danilo Vasconcellos Vargas, et al. ∙ 2 ∙ share

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Self Training Autonomous Driving Agent

Intrinsically, driving is a Markov Decision Process which suits well the...
04/26/2019 ∙ by Shashank Kotyan, et al. ∙ 0 ∙ share

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Batch Tournament Selection for Genetic Programming

Lexicase selection achieves very good solution quality by introducing or...
04/18/2019 ∙ by Vinicius V. Melo, et al. ∙ 0 ∙ share

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Tackling Unit Commitment and Load Dispatch Problems Considering All Constraints with Evolutionary Computation

Unit commitment and load dispatch problems are important and complex pro...
03/06/2019 ∙ by Danilo Vasconcellos Vargas, et al. ∙ 0 ∙ share

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Understanding the One-Pixel Attack: Propagation Maps and Locality Analysis

Deep neural networks were shown to be vulnerable to single pixel modific...
02/08/2019 ∙ by Danilo Vasconcellos Vargas, et al. ∙ 12 ∙ share

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Universal Rules for Fooling Deep Neural Networks based Text Classification

Recently, deep learning based natural language processing techniques are...
01/22/2019 ∙ by Di Li, et al. ∙ 0 ∙ share

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Spectrum-Diverse Neuroevolution with Unified Neural Models

Learning algorithms are being increasingly adopted in various applicatio...
01/06/2019 ∙ by Danilo Vasconcellos Vargas, et al. ∙ 0 ∙ share

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General Subpopulation Framework and Taming the Conflict Inside Populations

Structured evolutionary algorithms have been investigated for some time....
01/02/2019 ∙ by Danilo Vasconcellos Vargas, et al. ∙ 0 ∙ share

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Self Organizing Classifiers and Niched Fitness

Learning classifier systems are adaptive learning systems which have bee...
11/20/2018 ∙ by Danilo Vasconcellos Vargas, et al. ∙ 0 ∙ share

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Self Organizing Classifiers: First Steps in Structured Evolutionary Machine Learning

Learning classifier systems (LCSs) are evolutionary machine learning alg...
11/20/2018 ∙ by Danilo Vasconcellos Vargas, et al. ∙ 6 ∙ share

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Contingency Training

When applied to high-dimensional datasets, feature selection algorithms ...
11/20/2018 ∙ by Danilo Vasconcellos Vargas, et al. ∙ 0 ∙ share

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Novelty-organizing team of classifiers in noisy and dynamic environments

In the real world, the environment is constantly changing with the input...
09/19/2018 ∙ by Danilo Vasconcellos Vargas, et al. ∙ 0 ∙ share

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Attacking Convolutional Neural Network using Differential Evolution

The output of Convolutional Neural Networks (CNN) has been shown to be d...
04/19/2018 ∙ by Jiawei Su, et al. ∙ 0 ∙ share

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Lightweight Classification of IoT Malware based on Image Recognition

The Internet of Things (IoT) is an extension of the traditional Internet...
02/11/2018 ∙ by Jiawei Su, et al. ∙ 0 ∙ share

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One pixel attack for fooling deep neural networks

Recent research has revealed that the output of Deep Neural Networks (DN...
10/24/2017 ∙ by Jiawei Su, et al. ∙ 0 ∙ share

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