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20232026
most citedNonstationary Time Series Forecasting via Unknown Distribution Adaptation

1 citations · 2 across the 9 of their papers we have counts for

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5 papers · 1 filter

cs.LG2024

Learning Discrete Latent Variable Structures with Tensor Rank Conditions

Zhengming Chen, Ruichu Cai, Feng Xie +5

Unobserved discrete data are ubiquitous in many scientific disciplines, and how to learn the causal structure of these latent variables is crucial for uncovering data patterns. Mos…

cs.CL2024

HateDebias: On the Diversity and Variability of Hate Speech Debiasing

Hongyan Wu, Zhengming Chen, Zijian Li +4

Hate speech frequently appears on social media platforms and urgently needs to be effectively controlled. Alleviating the bias caused by hate speech can help resolve various ethica…

cs.LG2024

Automating the Selection of Proxy Variables of Unmeasured Confounders

Feng Xie, Zhengming Chen, Shanshan Luo +3

Recently, interest has grown in the use of proxy variables of unobserved confounding for inferring the causal effect in the presence of unmeasured confounders from observational da…

stat.ML2024

Causal Discovery from Poisson Branching Structural Causal Model Using High-Order Cumulant with Path Analysis

Jie Qiao, Yu Xiang, Zhengming Chen +2

Count data naturally arise in many fields, such as finance, neuroscience, and epidemiology, and discovering causal structure among count data is a crucial task in various scientifi…

cs.LG2024★ 1 cited

Nonstationary Time Series Forecasting via Unknown Distribution Adaptation

Zijian Li, Ruichu Cai, Zhenhui Yang +6

As environments evolve, temporal distribution shifts can degrade time series forecasting performance. A straightforward solution is to adapt to nonstationary changes while preservi…