8 citations · 13 across the 6 of their papers we have counts for
7 papers
Algorithmic Harms Associated with Generative Model-Augmented Recommendation Systems
Christine Herlihy, Xumei Xi, Shloka Desai +2
In this work, we consider algorithmic harms that may arise as generative models are incorporated into machine learning platforms. We argue that existing harm taxonomies and threat…
Entry-Specific Matrix Estimation under Arbitrary Sampling Patterns through the Lens of Network Flows
Yudong Chen, Xumei Xi, Christina Lee Yu
Matrix completion tackles the task of predicting missing values in a low-rank matrix based on a sparse set of observed entries. It is often assumed that the observation pattern is…
Entry-Specific Bounds for Low-Rank Matrix Completion under Highly Non-Uniform Sampling
Xumei Xi, Christina Lee Yu, Yudong Chen
Low-rank matrix completion concerns the problem of estimating unobserved entries in a matrix using a sparse set of observed entries. We consider the non-uniform setting where the o…
Integrating Offline Reinforcement Learning with Transformers for Sequential Recommendation
Xumei Xi, Yuke Zhao, Quan Liu +2
We consider the problem of sequential recommendation, where the current recommendation is made based on past interactions. This recommendation task requires efficient processing of…
Matrix Estimation for Offline Reinforcement Learning with Low-Rank Structure
Xumei Xi, Christina Lee Yu, Yudong Chen
We consider offline Reinforcement Learning (RL), where the agent does not interact with the environment and must rely on offline data collected using a behavior policy. Previous wo…
Local Minima Structures in Gaussian Mixture Models
Yudong Chen, Dogyoon Song, Xumei Xi +1
We investigate the landscape of the negative log-likelihood function of Gaussian Mixture Models (GMMs) with a general number of components in the population limit. As the objective…
Tensor Completion with Nearly Linear Samples Given Weak Side Information
Christina Lee Yu, Xumei Xi
Tensor completion exhibits an interesting computational-statistical gap in terms of the number of samples needed to perform tensor estimation. While there are only degrees…