Donnerstag, 05. Dezember 2024, 16:45 - 18:15 iCal
Invited Talk: Timour Igamberdiev
Privacy-preserving Natural Language Processing
Hörsaal 33 (HS) im Hauptgebäude der Universität Wien
Universitätsring 1, 1010 Wien
Vortrag
Abstract: In today's world, the protection of privacy is increasingly gaining attention, not only among the general public, but also within the fields of machine learning and natural language processing (NLP). An established gold standard for providing a guarantee of privacy protection to all individuals in a dataset is the framework of differential privacy (DP). Intuitively, differential privacy provides a formal theoretical guarantee that the contribution of any individual to some analysis on a dataset is bounded. In other words, no single individual can influence this analysis 'too much'.
In this lecture we will first discuss why privacy is important and the consequences of not using privacy-preserving methods with sensitive data. We will go through some key theoretical background on differential privacy, discussing fundamental concepts in the field such as the randomized response technique, formal and informal definitions of differential privacy, as well as how to achieve a DP guarantee for an algorithm. We will finally delve into applications of DP to the fields of machine learning and NLP, in particular with the algorithm Differentially Private Stochastic Gradient Descent (DP-SGD).
Bio: Timour is a postdoctoral researcher in the Natural Language Processing research group led by Prof. Benjamin Roth, part of the Data Mining and Machine Learning group of the Faculty of Computer Science, University of Vienna. He completed his Ph.D. in Computer Science at the Technical University of Darmstadt in 2023 under the supervision of Prof. Ivan Habernal and continued to work there as a postdoctoral researcher until late 2024. His research expertise is on privacy-preserving natural language processing, with a focus on differential privacy for NLP systems and textual data. He has further worked with graph-based deep learning and figurative language processing.
Veranstalter
Lecture series: Machines that understand? Large Language Models and Artificial Intelligence
Kontakt
Lukas Thoma
Universität Wien
Forschungsgruppe Data Mining and Machine Learning
+43-1-4277-79501
lukas.thoma@univie.ac.at
Erstellt am Donnerstag, 24. Oktober 2024, 18:34
Letzte Änderung am Dienstag, 29. Oktober 2024, 08:58