Search Results for author: Yuantong Li

Found 8 papers, 0 papers with code

Double Matching Under Complementary Preferences

no code implementations24 Jan 2023 Yuantong Li, Guang Cheng, Xiaowu Dai

In this paper, we propose a new algorithm for addressing the problem of matching markets with complementary preferences, where agents' preferences are unknown a priori and must be learned from data.

Thompson Sampling

Graph Federated Learning with Hidden Representation Sharing

no code implementations23 Dec 2022 Shuang Wu, Mingxuan Zhang, Yuantong Li, Carl Yang, Pan Li

On the other hand, due to the increasing demands for the protection of clients' data privacy, Federated Learning (FL) has been widely adopted: FL requires models to be trained in a multi-client system and restricts sharing of raw data among clients.

Federated Learning

Debiasing Neural Retrieval via In-batch Balancing Regularization

no code implementations NAACL (GeBNLP) 2022 Yuantong Li, Xiaokai Wei, Zijian Wang, Shen Wang, Parminder Bhatia, Xiaofei Ma, Andrew Arnold

People frequently interact with information retrieval (IR) systems, however, IR models exhibit biases and discrimination towards various demographics.

Fairness Passage Retrieval +1

Rate-Optimal Contextual Online Matching Bandit

no code implementations7 May 2022 Yuantong Li, Chi-Hua Wang, Guang Cheng, Will Wei Sun

Existing works focus on multi-armed bandit with static preference, but this is insufficient: the two-sided preference changes as along as one-side's contextual information updates, resulting in non-static matching.

Residual Bootstrap Exploration for Stochastic Linear Bandit

no code implementations23 Feb 2022 Shuang Wu, Chi-Hua Wang, Yuantong Li, Guang Cheng

We propose a new bootstrap-based online algorithm for stochastic linear bandit problems.

Computational Efficiency

Online Bootstrap Inference For Policy Evaluation in Reinforcement Learning

no code implementations8 Aug 2021 Pratik Ramprasad, Yuantong Li, Zhuoran Yang, Zhaoran Wang, Will Wei Sun, Guang Cheng

The recent emergence of reinforcement learning has created a demand for robust statistical inference methods for the parameter estimates computed using these algorithms.

reinforcement-learning Reinforcement Learning (RL)

Online Forgetting Process for Linear Regression Models

no code implementations3 Dec 2020 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 time.


A Non-Iterative Quantile Change Detection Method in Mixture Model with Heavy-Tailed Components

no code implementations19 Jun 2020 Yuantong Li, Qi Ma, Sujit K. Ghosh

Estimating parameters of mixture model has wide applications ranging from classification problems to estimating of complex distributions.

Change Detection

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