Titlebook: ECML PKDD 2018 Workshops; Nemesis 2018, UrbRea Carlos Alzate,Anna Monreale,Mathieu Sinn Conference proceedings 2019 Springer Nature Switzer

Ondines-curse

Malcontent

Label Sanitization Against Label Flipping Poisoning Attacks can inject malicious data in the training dataset to subvert the learning process, compromising the performance of the algorithm producing errors in a targeted or an indiscriminate way. Label flipping attacks are a special case of data poisoning, where the attacker can control the labels assigned t

humectant

Limitations of the Lipschitz Constant as a Defense Against Adversarial Examplesrecently proposed methods for computing the Lipschitz constant. We show that the Lipschitz constant may indeed enable adversarially robust neural networks. However, the methods currently employed for computing it suffer from theoretical and practical limitations. We argue that addressing this shortc

強有力

Understanding Adversarial Space Through the Lens of Attributionaltered original image, neural networks behave abnormally on these modified images. Image attribution methods highlight regions of input image important for the model’s prediction. We believe that the domains of adversarial generation and attribution are closely related and we support this claim by

聽覺

Detecting Potential Local Adversarial Examples for Human-Interpretable Defenseulate specific variables, such as the age or the salary, in order to get better chances of approval. In this ongoing work, we propose to discuss, with a first proposition, the issue of detecting a potential local adversarial example on classical tabular data by providing to a human expert the locall

Canary

Smart Cities with Deep Edges in IoT and smart cities. This will enable a considerable increase in the analytics and urban reasoning that can take place at the edge of the network. The end-to-end latency for these models will also be reduced due to the physical proximity of the edge devices, which allows reasoning one hop away

Conduit

ANT

Object Geolocation from Crowdsourced Street Level Imageryexperiments with imagery from Mapillary crowdsourcing platform demonstrate that with increasing amount of images, the detection accuracy is getting close to that obtained with high-end street level data. Nevertheless, due to excessive camera position noise, the estimated geolocation (position) of th

山間窄路

Extending Support Vector Regression to Constraint Optimization: Application to the Reduction of Potestantial costs due to patient treatments. In addition, some recent studies have suggested that increasing the number of nurses in selected geographic areas could lead to the reduction of the rates of potentially avoidable hospitalizations in those areas. In the meantime, health authorities are highl

committed