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Dos Mil Tres Mil, 2017 El presente documento tiene como propósito efectuar una aproximación, desde el punto de vista jurisprudencial y legal, del desarrollo que ha tenido la prueba oficiosa en el sistema penal adversarial de tendencia acusatoria, implementado en Colombia con ...
Jimmy Patiño García +2 more
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A3T: Adversarially Augmented Adversarial Training
CoRR, 2018 accepted for an oral presentation in Machine Deception Workshop, NIPS ...
Akram Erraqabi +3 more
openaire +2 more sources
Frontiers in Neurorobotics, 2018 Many real-world decision-making problems involve multiple conflicting objectives that can not be optimized simultaneously without a compromise. Such problems are known as multi-objective Markov decision processes and they constitute a significant ...
Sherif Abdelfattah +2 more
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Generative adversarial networks [PDF]
Communications of the ACM, 2020 Generative adversarial networks are a kind of artificial intelligence algorithm designed to solve the generative modeling problem. The goal of a generative model is to study a collection of training examples and learn the probability distribution that generated them.
Ian J. Goodfellow +7 more
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On The Empirical Effectiveness of Unrealistic Adversarial Hardening Against Realistic Adversarial Attacks [PDF]
, 2023 While the literature on security attacks and defense of Machine Learning (ML) systems mostly focuses on unrealistic adversarial examples, recent research has raised concern about the under-explored field of realistic adversarial attacks and their ...
Simonetto, Thibault +6 more
core +1 more source
Targeted Universal Adversarial Examples for Remote Sensing
Remote Sensing, 2022 Researchers are focusing on the vulnerabilities of deep learning models for remote sensing; various attack methods have been proposed, including universal adversarial examples.
Tao Bai, Hao Wang, Bihan Wen
doaj +1 more source
Smooth adversarial examples [PDF]
EURASIP Journal on Information Security, 2020 AbstractThis paper investigates the visual quality of the adversarial examples. Recent papers propose to smooth the perturbations to get rid of high frequency artifacts. In this work, smoothing has a different meaning as it perceptually shapes the perturbation according to the visual content of the image to be attacked. The perturbation becomes locally
Zhang, Hanwei +3 more
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sml911/Adversarial-DNN: First Release
, 2020 Cooper graduate research on generative adversaries in adversarial ...
Stephen
core +1 more source
CoRR, 2022 Planning algorithms are used in computational systems to direct autonomous behavior. In a canonical application, for example, planning for autonomous vehicles is used to automate the static or continuous planning towards performance, resource management, or functional goals (e.g., arriving at the destination, managing fuel fuel consumption).
Valentin Vie +6 more
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Wasserstein Adversarial Robustness [PDF]
, 2020 Deep models, while being extremely flexible and accurate, are surprisingly vulnerable to ``small, imperceptible'' perturbations known as adversarial attacks.
Wu, Kaiwen
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