• 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