Master's program at the Faculty of Mathematics and Computer Science, University of Bucharest
Speaker: Andrei Pătrașcu (University of Bucharest) Abstract: Recent empirical results confirm that one-class (OC) classification methods remain among the most important learning strategies for anomaly detection. In this seminar, we will technically describe in detail multiple basic OC schemes such as OC-SVM and SVDD and their deep variants, in order to identify room of improvements …
Speaker: Andrei Pătrașcu (University of Bucharest) Abstract: We continue our adventure by investigating existing results with Robust Principal Component Analysis (RPCA) and its adaptation to existing deep neural networks. Required reading: ZHOU, Chong; PAFFENROTH, Randy C. Anomaly detection with robust deep autoencoders. In: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and …
Speaker: Andra Băltoiu (University of Bucharest) Abstract: We continue our investigation on the task of detecting outliers in networks, by looking at the concept of signal variation on a graph. Required reading: A. Sandryhaila and J. M. F. Moura, "Classification via regularization on graphs," 2013 IEEE Global Conference on Signal and Information Processing, Austin, TX, …
Speaker: Paul Irofti (University of Bucharest) Abstract: We continue our investigation on the task of detecting outliers in networks when dealing with big-data and investigate existing online and distributed solutions. Required reading: Miao, Xuedan, et al. "Distributed online one-class support vector machine for anomaly detection over networks." IEEE transactions on cybernetics 49.4 (2018): 1475-1488. Liu, …
Speaker: Andrei Pătrașcu (University of Bucharest) Abstract: We continue our adventure by investigating existing results using Gaussian Mixture Models (GMM) for anomaly detection and their adaptation to existing deep neural networks. Required reading: Zong, Bo, et al. "Deep autoencoding gaussian mixture model for unsupervised anomaly detection." (2018). Chapter 11 from Deisenroth, Marc Peter, A. Aldo …
Speaker: Andra Băltoiu (University of Bucharest) Abstract: After attending the "Summer School on Applied Harmonic Analysis and Machine Learning" in Genova, Andra will give us a short introduction on Optimal Transport in the attempt of finding new prospects for the anomaly detection problem.
Speaker: Marius Popescu (University of Bucharest) Abstract: We continue our adventure by investigating existing natural language processing results that deal with unmasking authorship and their application to anomaly detection. Required reading: M. Koppel, J. Schler, and E. Bonchek-Dokow. Measuring Differentiability: Unmasking Pseudonymous Authors. Journal of Machine Learning Research, 8:1261–1276, 2007. T.R. Ionescu, S. Smeureanu, B. …
Speaker: Sorin-Gabriel Radu (University of Bucharest) Abstract: Va fi prezentată o versiune extinsă a lucrări de licență ce va prezenta concepte de Return Orientated Programming, o tehnică de reciclare și combinare a bucăților de cod existent, curat, astfel încât cod nou, nedorit, în general de tip malware, să fie executat.
Speaker: Horia Velicu (BRD - Groupe Societe Generale) Abstract: Presentation of topics of interest for 2020, objectives and data available at BRD. Proposals for the themes for the applied research institute that will be sponsored this year. Presentation of the new BRD AI Hub.
POSTPONED UNTIL FURTHER NOTICE. Speaker: Ioan Constantin (Orange Romania) Abstract: A brief walkthrough some of the challenges in offering advanced cyber security solutions for Business and Critical Infrastructures, from a Managed Security Services Provider's standpoint. We'll talk threat detection and mitigation, the specifics of OT Security in Critical Infrastructure, compliance and best practices. We'll also …