Search Results for author: Shoubo Hu

Found 8 papers, 2 papers with code

Efficient Bayesian Optimization with Deep Kernel Learning and Transformer Pre-trained on Multiple Heterogeneous Datasets

no code implementations9 Aug 2023 Wenlong Lyu, Shoubo Hu, Jie Chuai, Zhitang Chen

Bayesian optimization (BO) is widely adopted in black-box optimization problems and it relies on a surrogate model to approximate the black-box response function.

Bayesian Optimization

Reframed GES with a Neural Conditional Dependence Measure

1 code implementation17 Jun 2022 Xinwei Shen, Shengyu Zhu, Jiji Zhang, Shoubo Hu, Zhitang Chen

In this paper, we revisit the Greedy Equivalence Search (GES) algorithm, which is widely cited as a score-based algorithm for learning the MEC of the underlying causal structure.

Causal Discovery Causal Inference

Rethinking Client Reweighting for Selfish Federated Learning

no code implementations29 Sep 2021 Ruichen Luo, Shoubo Hu, Lequan Yu

To this end, we study a new $\textit{selfish}$ variant of federated learning, in which the ultimate objective is to learn a model with optimal performance on internal clients $\textit{alone}$ instead of all clients.

Federated Learning Image Classification +4

Contrastive ACE: Domain Generalization Through Alignment of Causal Mechanisms

no code implementations2 Jun 2021 Yunqi Wang, Furui Liu, Zhitang Chen, Qing Lian, Shoubo Hu, Jianye Hao, Yik-Chung Wu

Domain generalization aims to learn knowledge invariant across different distributions while semantically meaningful for downstream tasks from multiple source domains, to improve the model's generalization ability on unseen target domains.

Domain Generalization

A Causal Direction Test for Heterogeneous Populations

no code implementations8 Jun 2020 Vahid Partovi Nia, Xinlin Li, Masoud Asgharian, Shoubo Hu, Zhitang Chen, Yanhui Geng

Our simulation result show that the proposed adjustment significantly improves the performance of the causal direction test statistic for heterogeneous data.

Clustering Decision Making

Domain Generalization via Multidomain Discriminant Analysis

no code implementations25 Jul 2019 Shoubo Hu, Kun Zhang, Zhitang Chen, Laiwan Chan

Domain generalization (DG) aims to incorporate knowledge from multiple source domains into a single model that could generalize well on unseen target domains.

Domain Generalization Learning Theory

A Kernel Embedding-based Approach for Nonstationary Causal Model Inference

no code implementations23 Sep 2018 Shoubo Hu, Zhitang Chen, Laiwan Chan

Although nonstationary data are more common in the real world, most existing causal discovery methods do not take nonstationarity into consideration.

Causal Discovery

Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models

1 code implementation NeurIPS 2018 Shoubo Hu, Zhitang Chen, Vahid Partovi Nia, Laiwan Chan, Yanhui Geng

The inference of the causal relationship between a pair of observed variables is a fundamental problem in science, and most existing approaches are based on one single causal model.

Causal Inference Clustering

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