Important: We assume a fundamental understanding of machine learning among the participants. A brief introduction to the specific domain will be included by each speaker.
1. Natural Language Processing: Learning Neural Networks to Solve Language Understanding Tasks by Barabara Plank, ITU
Deep neural networks have brought steep advances in many fields, including Natural Language Processing (NLP). But when it comes to transferring knowledge to new conditions, neural networks struggle. In this talk I will outline what makes natural language processing so challenging. I will delineate possible ways to go about these challenges.
About Barbara Plank
• Associate Professor at ITU (IT University of Copenhagen).
• PhD in Computational Linguistics, The Netherlands. Before joining ITU, Barbara held faculty positions at the University of Groningen (The Netherlands) and Copenhagen University (KU) and a postdoc position at KU and the University of Trento, Italy.
• Advisory board member for the European Association of Computational Linguistics (EACL).
• Chair of international conferences and workshops, e.g., Barbara is general chair of the 22nd Nordic Conference on Computational Linguistics NoDaLiDa 2019 in Turku, program co-chair for the EurNLP Summit (pronounce “your NLP”) 2019 in London, program co-chair for the first Women in Data Science conference in Copenhagen 2019 and workshop chair for the Association of Computational Linguistics (ACL) 2019 in Florence, Italy.
2. Machine learning technology: How to enhance decision-making abilities in real-time by Jan Kremer, Corti
At Corti, we imagine a future where every medical professional can perform at an elevated level thanks to a new kind of human-computer partnership. Corti provides this partnership by utilizing machine learning technology to enhance the decision-making abilities in real-time. In this talk Jan will present Corti’s current machine learning stack with demos of the system.
About Jan Kremer
• Head of Machine Learning at Corti.
• PhD in Machine Learning from the University of Copenhagen with research in transferable machine learning for astronomical models, afterwards worked in the industry as a Data Scientist for Adform.
Drinks and food will be provided between talks
Organizer: Inge Bender Koch, IDA AI