Explore the first part of a three-part video series on training Logical Neural Networks (LNNs) using primal-dual methods for neuro-symbolic reasoning. Delve into the research paper "Training Logical Neural Networks by Primal–Dual Methods for Neuro-Symbolic Reasoning" by Lu et al. (2021, IBM research). Learn about cutting-edge algorithms at the intersection of symbolic methods and deep learning, presented by Rohan Reddy Sambidi, Yao Ting Chen, and Joshua Noronha from Arizona State University. Gain insights into the latest advancements in artificial intelligence, including progress towards artificial general intelligence (AGI). Access contact information for the presenters and a link to the original paper for further exploration of this exciting field in machine learning and AI.
Training Logical Neural Networks via Primal-Dual Methods - Part 1
Overview
Syllabus
Training LNN's via Primal Dual Methods Pt 1 of 3
Taught by
Neuro Symbolic
Related Courses
-
Training Logical Neural Networks via Primal-Dual Methods - Part 3
-
Training LNNs via Primal Dual Methods - Part 2 of 3
-
Learning Logical Relationships with Neural Networks - Part 3
-
Introduction to Artificial Intelligence
5.0 -
Deep Ontological Networks: An Overview and Implementation
-
NeurASP: Model Training - Part 2
