Skip to main content
Home

Main navigation

  • Home
  • Series
  • People
  • Depts & Colleges
  • Open Education

Main navigation

  • Home
  • Series
  • People
  • Depts & Colleges
  • Open Education

Strachey Lecture: Integrating Logic, Probability and Neuro-Symbolic Reasoning using Probabilistic Soft Logic

Series
Strachey Lectures
Video Audio Embed
An overview of work on probabilistic soft logic (PSL), an SRL framework for large-scale collective, probabilistic reasoning in relational domains and a description of recent work which integrates neural and symbolic (NeSy) reasoning.

Our ability to collect, manipulate, analyze, and act on vast amounts of data is having a profound impact on all aspects of society. Much of this data is heterogeneous in nature and interlinked in a myriad of complex ways. From information integration to scientific discovery to computational social science, we need machine learning methods that are able to exploit both the inherent uncertainty and the innate structure in a domain. Statistical relational learning (SRL) is a subfield that builds on principles from probability theory and statistics to address uncertainty while incorporating tools from knowledge representation and logic to represent structure. In this talk, I’ll overview our work on probabilistic soft logic (PSL), an SRL framework for large-scale collective, probabilistic reasoning in relational domains. I’ll also describe recent work which integrates neural and symbolic (NeSy) reasoning. I’ll close by highlighting emerging opportunities (and challenges!) in realizing the effectiveness of data and structure for knowledge discovery.

Bio:

Lise Getoor is a Distinguished Professor in the Computer Science & Engineering Department at UC Santa Cruz, where she holds the Jack Baskin Endowed Chair in Computer Engineering. She is founding Director of the UC Santa Cruz Data Science Research Center and is a Fellow of ACM, AAAI, and IEEE. Her research areas include machine learning and reasoning under uncertainty and she has extensive experience with machine learning and probabilistic modeling methods for graph and network data. She has over 250 publications including 13 best paper awards. She has served as an elected board member of the International Machine Learning Society, on the Computing Research Association (CRA) Board, as Machine Learning Journal Action Editor, Associate Editor for the ACM Transactions of Knowledge Discovery from Data, JAIR Associate Editor, and on the AAAI Executive Council.. She is a Distinguished Alumna of the UC Santa Barbara Computer Science Department and received the UC Santa Cruz Women in Science & Engineering (WISE) award. She received her PhD from Stanford University in 2001, her MS from UC Berkeley, and her BS from UC Santa Barbara, and was a professor at the University of Maryland, College Park from 2001-2013.

THE STRACHEY LECTURES ARE GENEROUSLY SUPPORTED BY OxFORD ASSET MANAGEMENT

More in this series

View Series
Strachey Lectures
Captioned

Strachey Lecture: How Are New Technologies Changing What We See?

There has been a proliferation of technological developments in the last few years that are beginning to improve how we perceive, attend to, notice, analyse and remember events, people, data and other information.
Previous
Strachey Lectures
Captioned

Strachey Lecture: Symmetry and Similarity

An introduction to algorithmic aspects of symmetry and similarity, ranging from the fundamental complexity theoretic "Graph Isomorphism Problem" to applications in optimisation and machine learning
Next
Transcript Available

Episode Information

Series
Strachey Lectures
People
Lise Getoor
Keywords
logic
reasoning
neural
symbolic
data
society
computational social science
Department: Department of Computer Science
Date Added: 27/10/2022
Duration: 01:03:39

Subscribe

Apple Podcast Video Apple Podcast Audio Audio RSS Feed Video RSS Feed

Download

Download Video Download Audio Download Transcript

Footer

  • About
  • Accessibility
  • Contribute
  • Copyright
  • Contact
  • Privacy
'Oxford Podcasts' Twitter Account @oxfordpodcasts | MediaPub Publishing Portal for Oxford Podcast Contributors | Upcoming Talks in Oxford | © 2011-2022 The University of Oxford