منابع مشابه
Adversarial Extreme Multi-label Classification
The goal in extreme multi-label classification is to learn a classifier which can assign a small subset of relevant labels to an instance from an extremely large set of target labels. Datasets in extreme classification exhibit a long tail of labels which have small number of positive training instances. In this work, we pose the learning task in extreme classification with large number of tail-...
متن کاملSupport Vector Machines Under Adversarial Label Noise
Battista Biggio [email protected] Dept. of Electrical and Electronic Engineering University of Cagliari Piazza d’Armi, 09123, Cagliari, Italy and Blaine Nelson [email protected] Dept. of Mathematics and Natural Sciences Eberhard-Karls-Universität Tübingen Sand 1, 72076, Tübingen, Germany and Pavel Laskov [email protected] Dept. of Mathematics and Natura...
متن کاملSupport vector machines under adversarial label contamination
Machine learning algorithms are increasingly being applied in security-related tasks such as spam and malware detection, although their security properties against deliberate attacks have not yet been widely understood. Intelligent and adaptive attackers may indeed exploit specific vulnerabilities exposed by machine learning techniques to violate system security. Being robust to adversarial dat...
متن کاملGeneralizing Adversarial Reinforcement Learning
Reinforcement Learning has been used for a number of years in single agent environments. This article reports on our investigation of Reinforcement Learning techniques in a multi-agent and adversarial environment with continuous observable state information. Our framework for evaluating algorithms is two-player hexagonal grid soccer. We introduce an extension to Prioritized Sweeping that allows...
متن کاملVariance Regularizing Adversarial Learning
We introduce a novel approach for training adversarial models by replacing the discriminator score with a bi-modal Gaussian distribution over the real/fake indicator variables. In order to do this, we train the Gaussian classifier to match the target bi-modal distribution implicitly through meta-adversarial training. We hypothesize that this approach ensures a nonzero gradient to the generator,...
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ژورنال
عنوان ژورنال: Proceedings of the AAAI Conference on Artificial Intelligence
سال: 2019
ISSN: 2374-3468,2159-5399
DOI: 10.1609/aaai.v33i01.33013183