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IMPORTANCE OF THE BURDEN OF ASSERTION FOR THE DEVELOPMENT OF THE ADVERSARIAL PROCESS

Jose Marcelo Menezes VIGLIAR

Objectives: This article analyzes the significance of procedural burdens as they relate to the development of the adversarial process, and in particular, the burden of assertion by the plaintiff. It points out that even in positive procedural situations, ... see more

Procedural burdens | Burden of assertion | Procedural situations | Adversarial process.

Revista JurÍdica , 2022

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Predicting extreme events in the stock market using generative adversarial networks

(1) Badre Labiad (Equipe AMIPS, Ecole Mohammadia d’Ingénieurs, Mohammed V University in Rabat, Morocco) (2) Abdelaziz Berrado (Equipe AMIPS, Ecole Mohammadia d’Ingénieurs, Mohammed V University in Rabat, Morocco) (3) Loubna Benabbou (Université du Québec à Rimouski (UQAR), Campus de Lévis, Canada)

Accurately predicting extreme stock market fluctuations at the right time will allow traders and investors to make better-informed investment decisions and practice more efficient financial risk management. However, extreme stock market events are particu... see more

Extreme events prediction | Time series generation | Stock markets simulation | Generative adversarial networks | Long short-term memory

International Journal of Advances in Intelligent Informatics , 2023

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Predicting extreme events in the stock market using generative adversarial networks

Extreme events prediction | Time series generation | Stock markets simulation | Generative adversarial networks | Long short-term memory

IJAIN (International Journal of Advances in Intelligent Informatics) , 2023

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Towards Generating Unit Test Codes Using Generative Adversarial Networks

Muhammad Johan Alibasa

Unit testing is one of the critical software development steps to ensure the software’s quality. Unit testing is often neglected despite its importance since it requires a significant amount of time and effort from the software developers to write them. E... see more

unit test | code generation | generative adversarial network

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) , 2022

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Parámetros para la evaluación de la enseñanza universitaria del Derecho Penal Adversarial en México Parameters for the evaluation of university teaching of adversarial criminal law in Mexico

Mariana Duran Márquez, Héctor Manuel Guzmán Ruíz, Juan Carlos Barrios Lira

Al considerar como hipótesis que el entendimiento y la práctica del derecho determinan la enseñanza de este último, y atendiendo a los trascendentes cambios que ha experimentado el sistema jurídico mexicano en materia de proceso penal acusatorio, este tra... see more

Enseñanza universitaria | sistema penal acusatorio | formación de operadores jurídicos | modelos de justicia oral | justicia adversarial

Revista PedagogÍa Universitaria y Didáctica del Derecho , 2097

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Reducing Adversarial Vulnerability through Adaptive Training Batch Size

Ken Sasongko,Adila Alfa Krisnadhi,Mohamad Ivan Fanany

Neural networks possess an ability to generalize well to data distribution, to an extent that they are capable of fitting to a randomly labeled data. But they are also known to be extremely sensitive to adversarial examples. Batch Normalization (BatchNorm... see more

adversarial examples | batch normalization | fixup initialization | batch size variation

Jurnal Ilmu Komputer dan Informasi , 2021

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A Survey of Adversarial Machine Learning in Cyber Warfare

Vasisht Duddu

The changing nature of warfare has seen a paradigm shift from the conventional to asymmetric, contactless warfare such as information and cyber warfare. Excessive dependence on information and communication technologies, cloud infrastructures, big data an... see more

Adversarial machine learning | Adversary modelling | Cyber attacks | Security | Privacy

Defence Science Journal , PP

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SCOPING ADVERSARIAL ATTACK FOR IMPROVING ITS QUALITY

K. S. Khabarlak,L. S. Koriashkina

Context. The subject of this paper is adversarial attacks, their types, reasons for the emergence. A simplified fast and effective logistic regression attack algorithm has been presented. The work’s relevance is explained by the fact that neural network’s... see more

adversarial attacks | fast adversarial attack algorithm | logistic regression | neural network vulnerabilities.

Radìoelektronika, Ìnformatika, Upravlìnnâ , 2019

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ROBUSTNESS OF DEEP NEURAL NETWORKS TO ADVERSARIAL EXAMPLES

Da Teng,Xiao Song,Guanghong Gong,liang Han

Deep neural networks have achieved state-of-the-art performance in many artificial intelligence areas, such as object recognition, speech recognition and machine translation. While the deep neural networks have high expression capabilities, they are prone... see more

machine learning | deep learning | neural networks | adversarial examples

International Journal of Industrial Engineering: Theory; Applications and Practice , 2017

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