Protocols in Dynamic Epistemic Logic

Facultatea de Matematica si Informatica, sala 202

Speaker:  Alexandru Dragomir (University of Bucharest) Abstract: Dynamic epistemic logics are useful in reasoning about knowledge and certain acts of learning (epistemic actions). However, not all epistemic actions are allowed

Dynamic Code Analysis

Speaker:  Radu Velea (BitDefender) Abstract: Static code analysis methods have the advantage of providing deterministic and reliable results. Malware has evolved beyond the point where simple pattern matching algorithms or

Anomaly Detection Reading Group: Deep OC-SVM

Facultatea de Matematica si Informatica, sala 202

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

Anomaly Detection Reading Group: Deep RPCA

Facultatea de Matematica si Informatica, sala 202

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

Anomaly Detection Reading Group: Graph Classification

Facultatea de Matematica si Informatica, sala Google

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.

Anomaly Detection Reading Group: Distributed Online AD

Facultatea de Matematica si Informatica, sala Google

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.

Anomaly Detection Reading Group: Gaussian Mixture Models

Facultatea de Matematica si Informatica, sala 202

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

Optimal Transport for (Unsupervised) Machine Learning

Facultatea de Matematica si Informatica, sala Google

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