Denoising Diffusion Recommender Model - Lecture 2.2
Offered By: Association for Computing Machinery (ACM) via YouTube
Course Description
Overview
Explore a cutting-edge conference talk on the Denoising Diffusion Recommender Model presented at SIGIR 2024. Delve into the innovative application of diffusion models in recommender systems, as discussed by authors Jujia Zhao, Wenjie Wang, Yiyan Xu, Teng Sun, Fuli Feng, and Tat-Seng Chua. In this 15-minute presentation, gain insights into how denoising diffusion techniques are being leveraged to enhance recommendation algorithms and improve personalized content delivery. Learn about the latest advancements in this field and understand the potential impact on future recommender system technologies.
Syllabus
SIGIR 2024 T2.2 [fp] Denoising Diffusion Recommender Model
Taught by
Association for Computing Machinery (ACM)
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Artificial Intelligence for Robotics
Stanford University via Udacity Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent