This group is for everyone who loves and lives data science. If you have fun digging large amounts of data and you heart beats faster, when you have discovered an indication of a new pattern, if you like hacking and enjoy trying new technologies, then this group is the right for you. We like to meet you and discuss what is going on in the various companies around our domain.
Dies ist eine Gruppe für alle, die Data Science leben und lieben. Für alle, die Muster erkennen, wenn sie auf einen Bildschirm mit Zahlen starren, Spass daran haben, die neuesten Technologien auszuprobieren und nicht verzweifeln, wenn sie mal wieder den einen fießen Bug in ihrem Code suchen. Für dich, die du gerne Einblicke in die Welt der Daten und ihre Bedeutung gibst, egal ob tagtäglich in deinem Unternehmen oder demnächst in unserem Meet-up.
Recent years have seen strong improvements in language technologies such as spoken language understanding, machine reading comprehension, and question answering. A major beneficiary of these technologies are so-called dialogue systems, such as virtual personal assistants. While classically many of these systems were hand-crafted, machine learning components are essential today. This talk provides a high-level overview over machine learning approaches in dialogue systems. We introduce the main modules of the classical pipeline and how they can be replaced by data-driven models -- usually deep neural networks. Finally, we discuss open challenges posed by data and label scarcity, as well as inadequate automated metrics.
Hannes Schulz received a BSc in cognitive science from the university of Osnabrück and an MSc in computer science from the university of Freiburg. During his PhD in Bonn, Hannes worked on deep neural network technologies for image segmentation. Today, Hannes is a researcher at Microsoft Research Montreal, with a focus on dialogue systems.
Microsoft Research was founded in 1991, with the aim of doing fundamental computer research. Research at Microsoft today encompasses the Microsoft Research organization along with researchers and scientists who are embedded across the company. Researchers and scientists at Microsoft collaborate with Microsoft product and service teams, and with researchers and scientist from academic institutions and industrial researchers. The Montreal lab was founded in 2017. Engineers and researchers in the lab work on natural language processing, dialogue, reinforcement learning, and fairness and transparency.