Ruocheng Guo | DeepAI

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∙ 07/17/2023

Learning for Counterfactual Fairness from Observational Data

Fairness-aware machine learning has attracted a surge of attention in ma...

0 Jing Ma, et al. ∙

∙ 05/25/2023

Graph-Based Model-Agnostic Data Subsampling for Recommendation Systems

Data subsampling is widely used to speed up the training of large-scale ...

0 Xiaohui Chen, et al. ∙

∙ 03/11/2023

AutoMLP: Automated MLP for Sequential Recommendations

Sequential recommender systems aim to predict users' next interested ite...

0 Muyang Li, et al. ∙

∙ 10/16/2022

CLEAR: Generative Counterfactual Explanations on Graphs

Counterfactual explanations promote explainability in machine learning m...

0 Jing Ma, et al. ∙

∙ 04/25/2022

MLP4Rec: A Pure MLP Architecture for Sequential Recommendations

Self-attention models have achieved state-of-the-art performance in sequ...

0 Muyang Li, et al. ∙

∙ 01/10/2022

Learning Fair Node Representations with Graph Counterfactual Fairness

Fair machine learning aims to mitigate the biases of model predictions a...

69 Jing Ma, et al. ∙

∙ 01/16/2021

Out-of-distribution Prediction with Invariant Risk Minimization: The Limitation and An Effective Fix

This work considers the out-of-distribution (OOD) prediction problem whe...

0 Ruocheng Guo, et al. ∙

∙ 11/22/2019

Privacy-Aware Recommendation with Private-Attribute Protection using Adversarial Learning

Recommendation is one of the critical applications that helps users find...

0 Ghazaleh Beigi, et al. ∙

∙ 07/06/2019

I Am Not What I Write: Privacy Preserving Text Representation Learning

Online users generate tremendous amounts of textual information by parti...

0 Ghazaleh Beigi, et al. ∙

∙ 06/08/2019

Learning Individual Treatment Effects from Networked Observational Data

With convenient access to observational data, learning individual causal...

0 Ruocheng Guo, et al. ∙

∙ 05/04/2019

Detecting Pathogenic Social Media Accounts without Content or Network Structure

The spread of harmful mis-information in social media is a pressing prob...

0 Elham Shaabani, et al. ∙

∙ 11/23/2018

Protecting User Privacy: An Approach for Untraceable Web Browsing History and Unambiguous User Profiles

The overturning of the Internet Privacy Rules by the Federal Communicati...

0 Ghazaleh Beigi, et al. ∙

∙ 09/25/2018

A Survey of Learning Causality with Data: Problems and Methods

The era of big data provides researchers with convenient access to copio...

0 Ruocheng Guo, et al. ∙

∙ 08/09/2018

Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects

Modeling spillover effects from observational data is an important probl...

0 Vineeth Rakesh, et al. ∙

∙ 12/25/2017

Strongly Hierarchical Factorization Machines and ANOVA Kernel Regression

High-order parametric models that include terms for feature interactions...

0 Ruocheng Guo, et al. ∙

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