PRiML Seminar Series: Fernando Pereira

Berger Auditorium

September 25, 2019

11:00 AM - 12:00 PM

Title: Representation learning and the challenge of reasoning

Abstract: Advances in machine learning (ML) have led to a golden age of increasingly rich models of language with large experimental gains in many language understanding tasks. In the midst of this plenty, we are also getting a better sense of where these new methods fall short. I will walk you through a collection of examples that are obvious for people but pose unsolved simple reasoning challenges to current ML methods. I will conclude with a few suggestions on how ML might be guided to learn useful reasoning patterns.

Bio: Fernando Pereira is VP and Engineering Fellow at Google, where he leads research and development in natural language understanding and machine learning. His previous positions include chair of the Computer and Information Science department of the University of Pennsylvania, head of the Machine Learning and Information Retrieval department at AT&T Labs, and research and management positions at SRI International. He received a Ph.D. in Artificial Intelligence from the University of Edinburgh in 1982, and has over 120 research publications on computational linguistics, machine learning, bioinformatics, speech recognition, and logic programming, as well as several patents.  He was elected AAAI Fellow in 1991 for contributions to computational linguistics and logic programming, ACM Fellow in 2010 for contributions to machine learning models of natural language and biological sequences, ACL Fellow for contributions to sequence modeling, finite-state methods, and dependency and deductive parsing, and to the American Philosophical Society in 2019.  He was president of the Association for Computational Linguistics in 1993.