2 citations · 4 across the 12 of their papers we have counts for
12 papers
MBD: A Model-Based Debiasing Framework Across User, Content, and Model Dimensions
Yuantong Li, Lei Yuan, Zhihao Zheng +27
Modern recommendation systems rank candidates by aggregating multiple behavioral signals through a value model. However, many commonly used signals are inherently affected by heter…
Epinet for Content Cold Start
Hong Jun Jeon, Songbin Liu, Yuantong Li +5
The exploding popularity of online content and its user base poses an evermore challenging matching problem for modern recommendation systems. Unlike other frontiers of machine lea…
Incentivized Exploration with Stochastic Covariates: A Two-Stage Mechanism Design for Recommender System
Yuantong Li, Guang Cheng, Xiaowu Dai
Recommender systems play a crucial role in internet economies by connecting users with relevant products. However, designing effective recommender systems faces the key challenges:…
Li, Li, and Dai's Contribution to the Discussion of "Estimating Means of Bounded Random Variables by Betting" by Waudby-Smith and Aaditya Ramdas
Yijia Li, Yuantong Li, Xiaowu Dai
We congratulate Waudby-Smith and Ramdas for their interesting paper \cite{waudbysmith2022estimating} in generating confidence intervals and time-uniform confidence sequences for me…
Two-sided Competing Matching Recommendation Markets With Quota and Complementary Preferences Constraints
Yuantong Li, Guang Cheng, Xiaowu Dai
In this paper, we propose a new recommendation algorithm for addressing the problem of two-sided online matching markets with complementary preferences and quota constraints, where…
Graph Federated Learning with Hidden Representation Sharing
Shuang Wu, Mingxuan Zhang, Yuantong Li +2
Learning on Graphs (LoG) is widely used in multi-client systems when each client has insufficient local data, and multiple clients have to share their raw data to learn a model of…
Debiasing Neural Retrieval via In-batch Balancing Regularization
Yuantong Li, Xiaokai Wei, Zijian Wang +4
People frequently interact with information retrieval (IR) systems, however, IR models exhibit biases and discrimination towards various demographics. The in-processing fair rankin…
Dynamic Matching Bandit For Two-Sided Online Markets
Yuantong Li, Chi-hua Wang, Guang Cheng +1
Two-sided online matching platforms are employed in various markets. However, agents' preferences in the current market are usually implicit and unknown, thus needing to be learned…
Residual Bootstrap Exploration for Stochastic Linear Bandit
Shuang Wu, Chi-Hua Wang, Yuantong Li +1
We propose a new bootstrap-based online algorithm for stochastic linear bandit problems. The key idea is to adopt residual bootstrap exploration, in which the agent estimates the n…
Online Bootstrap Inference For Policy Evaluation in Reinforcement Learning
Pratik Ramprasad, Yuantong Li, Zhuoran Yang +3
The recent emergence of reinforcement learning has created a demand for robust statistical inference methods for the parameter estimates computed using these algorithms. Existing m…
Online Forgetting Process for Linear Regression Models
Yuantong Li, Chi-hua Wang, Guang Cheng
Motivated by the EU's "Right To Be Forgotten" regulation, we initiate a study of statistical data deletion problems where users' data are accessible only for a limited period of ti…
A Non-Iterative Quantile Change Detection Method in Mixture Model with Heavy-Tailed Components
Yuantong Li, Qi Ma, Sujit K. Ghosh
Estimating parameters of mixture model has wide applications ranging from classification problems to estimating of complex distributions. Most of the current literature on estimati…