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Publikováno v:
Expert Systems with Applications 97 (2018): 18-40
Classifiers operating in a dynamic, real world environment, are vulnerable to adversarial activity, which causes the data distribution to change over time. These changes are traditionally referred to as concept drift, and several approaches have been
Externí odkaz:
http://arxiv.org/abs/1803.09160
Operating in a dynamic real world environment requires a forward thinking and adversarial aware design for classifiers, beyond fitting the model to the training data. In such scenarios, it is necessary to make classifiers - a) harder to evade, b) eas
Externí odkaz:
http://arxiv.org/abs/1803.09162
The increasing scale and sophistication of cyberattacks has led to the adoption of machine learning based classification techniques, at the core of cybersecurity systems. These techniques promise scale and accuracy, which traditional rule or signatur
Externí odkaz:
http://arxiv.org/abs/1803.09163
Classifiers deployed in the real world operate in a dynamic environment, where the data distribution can change over time. These changes, referred to as concept drift, can cause the predictive performance of the classifier to drop over time, thereby
Externí odkaz:
http://arxiv.org/abs/1704.00023
Autor:
Lyu, Lingyu, Kantardzic, Mehmed
With the popularity of massive open online courses, grading through crowdsourcing has become a prevalent approach towards large scale classes. However, for getting grades for complex tasks, which require specific skills and efforts for grading, crowd
Externí odkaz:
http://arxiv.org/abs/1703.10579
While modern day web applications aim to create impact at the civilization level, they have become vulnerable to adversarial activity, where the next cyber-attack can take any shape and can originate from anywhere. The increasing scale and sophistica
Externí odkaz:
http://arxiv.org/abs/1703.07909
Autor:
Emara, Wael, Kantardzic, Mehmed
In this work we present a quadratic programming approximation of the Semi-Supervised Support Vector Machine (S3VM) problem, namely approximate QP-S3VM, that can be efficiently solved using off the shelf optimization packages. We prove that this appro
Externí odkaz:
http://arxiv.org/abs/1107.5236
Autor:
Rojkova, Viktoria, Kantardzic, Mehmed
To observe the evolution of network traffic correlations we analyze the eigenvalue spectra and eigenvectors statistics of delayed correlation matrices of network traffic counts time series. Delayed correlation matrix D is composed of the correlations
Externí odkaz:
http://arxiv.org/abs/0707.1083