Tao Lin
  • Bio
  • News
  • Research
  • Publications
  • Talks
  • Experience
  • Recent & Upcoming Talks
    • Example Talk
  • Publications
    • Generalized Principal-Agent Problem with a Learning Agent
    • Information Design with Unknown Prior
    • User-Creator Feature Polarization in Recommender Systems with Dual Influence
    • Bias Detection via Signaling
    • Multi-Sender Persuasion: A Computational Perspective
    • Learning Thresholds with Latent Values and Censored Feedback
    • Sample Complexity of Forecast Aggregation
    • From Monopoly to Competition: Optimal Contests Prevail
    • Nash Convergence of Mean-Based Learning Algorithms in First Price Auctions
    • How Many Representatives Do We Need? The Optimal Size of a Congress Voting on Binary Issues
    • Learning Utilities and Equilibria in Non-Truthful Auctions
    • A Game-Theoretic Analysis of the Empirical Revenue Maximization Algorithm with Endogenous Sampling
    • Private Data Manipulation in Optimal Sponsored Search Auction
  • Working Papers
    • Learning a Game by Paying the Agents
  • Recent & Upcoming Talks
    • How to Avoid Polarization in Recommender Systems with Dual Influence?
    • Bayesian Persuasion with a Learning Agent
    • Generalized Principal-Agent Problem with a Learning Agent
    • Private Data Manipulation in Sponsored Search Auctions
    • Sample Complexity of Forecast Aggregation
    • Persuading a Behavioral Agent: Approximately Best Responding and Learning
    • Nash Convergence of Mean-Based Learning Algorithms in First Price Auctions
    • Robustness of Empirical Revenue Maximization in Auction Learning
  • Projects
  • Journal Publications
    • From Monopoly to Competition: When Do Optimal Contests Prevail?
  • Blog
    • ๐ŸŽ‰ Easily create your own simple yet highly customizable blog
    • ๐Ÿง  Sharpen your thinking with a second brain
    • ๐Ÿ“ˆ Communicate your results effectively with the best data visualizations
    • ๐Ÿ‘ฉ๐Ÿผโ€๐Ÿซ Teach academic courses
    • โœ… Manage your projects
  • Example_projects
    • Pandas
    • PyTorch
    • scikit-learn
  • Experience
  • Teaching
    • Learn JavaScript
    • Learn Python
  • Notes
    • How Does Independence Help Generalization? Sample Complexity of ERM on Product Distributions
    • On Clearing Prices in Matching Markets: A Simple Characterization without Duality
  • Example_publications
    • An example preprint / working paper
    • An example journal article
    • An example conference paper

How to Avoid Polarization in Recommender Systems with Dual Influence?

Nov 15, 2024ยท
Tao Lin
Tao Lin
ยท 0 min read
Slides
Abstract
Presentation for our NeurIPS paper “User-Creator Feature Polarization in Recommender Systems with Dual Influence”.
Event
Computer Science and Engineering Seminar at CUHK
Location

Chinese University of Hong Kong,

Hong Kong, China

Last updated on Nov 15, 2024
Tao Lin
Authors
Tao Lin
PhD in Computer Science

Bayesian Persuasion with a Learning Agent Oct 20, 2024 →

ยฉ 2025 Me. This work is licensed under CC BY NC ND 4.0

Published with Hugo Blox Builder โ€” the free, open source website builder that empowers creators.