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MetaHKG: Meta Hyperbolic Learning for Few-shot Temporal Reasoning - M1.2

Offered By: Association for Computing Machinery (ACM) via YouTube

Tags

Knowledge Graphs Courses Artificial Intelligence Courses Data Mining Courses Machine Learning Courses Few-shot Learning Courses Information Retrieval Courses Meta-Learning Courses Hyperbolic Geometry Courses

Course Description

Overview

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Explore a conference talk on MetaHKG, a novel approach to meta hyperbolic learning for few-shot temporal reasoning in knowledge graphs. Delve into the research presented by authors Ruijie Wang, Yutong Zhang, Jinyang Li, and others at the SIGIR 2024 conference. Learn about the innovative techniques used to enhance reasoning capabilities in knowledge graphs with limited data. Gain insights into how hyperbolic geometry is leveraged to improve temporal reasoning tasks. Understand the potential applications and implications of this research for advancing artificial intelligence and machine learning in the field of information retrieval.

Syllabus

SIGIR 2024 M1.2 [fp] MetaHKG: Meta Hyperbolic Learning for Few-shot Temporal Reasoning


Taught by

Association for Computing Machinery (ACM)

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