b'Guandong Xu'

research

∙ 08/24/2023

Towards Communication-Efficient Model Updating for On-Device Session-Based Recommendation

On-device recommender systems recently have garnered increasing attentio...

0 Xin Xia, et al. ∙

research

∙ 08/09/2023

LLaMA-E: Empowering E-commerce Authoring with Multi-Aspect Instruction Following

E-commerce authoring involves creating attractive, abundant, and targete...

0 Kaize Shi, et al. ∙

research

∙ 07/10/2023

Counterfactual Explanation for Fairness in Recommendation

Fairness-aware recommendation eliminates discrimination issues to build ...

0 Xiangmeng Wang, et al. ∙

research

∙ 07/10/2023

Causal Neural Graph Collaborative Filtering

Graph collaborative filtering (GCF) has gained considerable attention in...

0 Xiangmeng Wang, et al. ∙

research

∙ 04/23/2023

Improved Churn Causal Analysis Through Restrained High-Dimensional Feature Space Effects in Financial Institutions

Customer churn describes terminating a relationship with a business or r...

0 David Hason Rudd, et al. ∙

research

∙ 04/20/2023

Causal Analysis of Customer Churn Using Deep Learning

Customer churn describes terminating a relationship with a business or r...

0 David Hason Rudd, et al. ∙

research

∙ 04/08/2023

Model-Agnostic Decentralized Collaborative Learning for On-Device POI Recommendation

As an indispensable personalized service in Location-based Social Networ...

0 Jing Long, et al. ∙

research

∙ 03/26/2023

CeFlow: A Robust and Efficient Counterfactual Explanation Framework for Tabular Data using Normalizing Flows

Counterfactual explanation is a form of interpretable machine learning t...

0 Tri Dung Duong, et al. ∙

research

∙ 03/26/2023

Achieving Counterfactual Fairness with Imperfect Structural Causal Model

Counterfactual fairness alleviates the discrimination between the model ...

0 Tri Dung Duong, et al. ∙

research

∙ 12/22/2022

Self-supervised Hypergraph Representation Learning for Sociological Analysis

Modern sociology has profoundly uncovered many convincing social criteri...

0 Xiangguo Sun, et al. ∙

research

∙ 11/08/2022

COV19IR : COVID-19 Domain Literature Information Retrieval

Increasing number of COVID-19 research literatures cause new challenges ...

0 Arusarka Bose, et al. ∙

research

∙ 09/06/2022

Being Automated or Not? Risk Identification of Occupations with Graph Neural Networks

The rapid advances in automation technologies, such as artificial intell...

0 Dawei Xu, et al. ∙

research

∙ 07/24/2022

Federated Graph Contrastive Learning

Graph learning models are critical tools for researchers to explore grap...

0 Haoran Yang, et al. ∙

research

∙ 07/14/2022

Reinforced Path Reasoning for Counterfactual Explainable Recommendation

Counterfactual explanations interpret the recommendation mechanism via e...

0 Xiangmeng Wang, et al. ∙

research

∙ 07/01/2022

Generating Counterfactual Hard Negative Samples for Graph Contrastive Learning

Graph contrastive learning has emerged as a powerful tool for unsupervis...

0 Haoran Yang, et al. ∙

research

∙ 04/23/2022

On-Device Next-Item Recommendation with Self-Supervised Knowledge Distillation

Modern recommender systems operate in a fully server-based fashion. To c...

0 Xin Xia, et al. ∙

research

∙ 02/17/2022

Graph Masked Autoencoder

Transformers have achieved state-of-the-art performance in learning grap...

0 Hongxu Chen, et al. ∙

research

∙ 02/14/2022

What Do They Capture? – A Structural Analysis of Pre-Trained Language Models for Source Code

Recently, many pre-trained language models for source code have been pro...

0 Yao Wan, et al. ∙

research

∙ 01/20/2022

Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation

Graph contrastive learning is the state-of-the-art unsupervised graph re...

0 Sixiao Zhang, et al. ∙

research

∙ 01/19/2022

Cross-Language Binary-Source Code Matching with Intermediate Representations

Binary-source code matching plays an important role in many security and...

0 Yi Gui, et al. ∙

research

∙ 01/19/2022

Dual Space Graph Contrastive Learning

Unsupervised graph representation learning has emerged as a powerful too...

26 Haoran Yang, et al. ∙

research

∙ 11/24/2021

Reinforcement Learning based Path Exploration for Sequential Explainable Recommendation

Recent advances in path-based explainable recommendation systems have at...

5 Yicong Li, et al. ∙

research

∙ 09/07/2021

Hyper Meta-Path Contrastive Learning for Multi-Behavior Recommendation

User purchasing prediction with multi-behavior information remains a cha...

9 Haoran Yang, et al. ∙

research

∙ 05/28/2021

Stochastic Intervention for Causal Inference via Reinforcement Learning

Causal inference methods are widely applied in various decision-making d...

0 Tri Dung Duong, et al. ∙

research

∙ 05/27/2021

Stochastic Intervention for Causal Effect Estimation

Causal inference methods are widely applied in various decision-making d...

0 Tri Dung Duong, et al. ∙

research

∙ 05/23/2021

DepressionNet: A Novel Summarization Boosted Deep Framework for Depression Detection on Social Media

Twitter is currently a popular online social media platform which allows...

0 Hamad Zogan, et al. ∙

research

∙ 05/19/2021

Where are we in embedding spaces? A Comprehensive Analysis on Network Embedding Approaches for Recommender Systems

Hyperbolic space and hyperbolic embeddings are becoming a popular resear...

0 Sixiao Zhang, et al. ∙

research

∙ 05/17/2021

Be Causal: De-biasing Social Network Confounding in Recommendation

In recommendation systems, the existence of the missing-not-at-random (M...

0 Qian Li, et al. ∙

research

∙ 05/03/2021

Prototype-based Counterfactual Explanation for Causal Classification

Counterfactual explanation is one branch of interpretable machine learni...

0 Tri Dung Duong, et al. ∙

research

∙ 04/19/2021

TFROM: A Two-sided Fairness-Aware Recommendation Model for Both Customers and Providers

At present, most research on the fairness of recommender systems is cond...

10 Yao Wu, et al. ∙

research

∙ 03/23/2021

A General Framework for Learning Prosodic-Enhanced Representation of Rap Lyrics

Learning and analyzing rap lyrics is a significant basis for many web ap...

4 Hongru Liang, et al. ∙

research

∙ 12/06/2020

NaturalCC: A Toolkit to Naturalize the Source Code Corpus

We present NaturalCC, an efficient and extensible toolkit to bridge the ...

0 Yao Wan, et al. ∙

research

∙ 12/02/2020

FAST: A Fairness Assured Service Recommendation Strategy Considering Service Capacity Constraint

An excessive number of customers often leads to a degradation in service...

0 Yao Wu, et al. ∙

research

∙ 09/14/2020

Leveraging Multi-level Dependency of Relational Sequences for Social Spammer Detection

Much recent research has shed light on the development of the relation-d...

0 Jun Yin, et al. ∙

research

∙ 07/05/2020

Detecting Community Depression Dynamics Due to COVID-19 Pandemic in Australia

The recent COVID-19 pandemic has caused unprecedented impact across the ...

0 Jianlong Zhou, et al. ∙

research

∙ 07/03/2020

Depression Detection with Multi-Modalities Using a Hybrid Deep Learning Model on Social Media

Social networks enable people to interact with one another by sharing in...

0 Hamad Zogan, et al. ∙

research

∙ 06/27/2020

Causality Learning: A New Perspective for Interpretable Machine Learning

Recent years have witnessed the rapid growth of machine learning in a wi...

0 Guandong Xu, et al. ∙

research

∙ 03/06/2020

TranS^3: A Transformer-based Framework for Unifying Code Summarization and Code Search

Code summarization and code search have been widely adopted in sofwarede...

0 Wenhua Wang, et al. ∙

research

∙ 11/26/2019

Generative Temporal Link Prediction via Self-tokenized Sequence Modeling

We formalize networks with evolving structures as temporal networks and ...

11 Yue Wang, et al. ∙

research

∙ 09/30/2019

Multi-Modal Attention Network Learning for Semantic Source Code Retrieval

Code retrieval techniques and tools have been playing a key role in faci...

0 Yao Wan, et al. ∙

research

∙ 08/10/2019

Social Influence-based Attentive Mavens Mining and Aggregative Representation Learning for Group Recommendation

Frequent group activities of human beings have become an indispensable p...

0 Peipei Wang, et al. ∙

research

∙ 11/17/2018

Improving Automatic Source Code Summarization via Deep Reinforcement Learning

Code summarization provides a high level natural language description of...

0 Yao Wan, et al. ∙

research

∙ 09/28/2018

Target-Independent Active Learning via Distribution-Splitting

To reduce the label complexity in Agnostic Active Learning (A^2 algorith...

0 Xiaofeng Cao, et al. ∙

research

∙ 07/24/2018

A Structured Perspective of Volumes on Active Learning

Active Learning (AL) is a learning task that requires learners interacti...

0 Xiaofeng Cao, et al. ∙

research

∙ 05/31/2018

Geometric Active Learning via Enclosing Ball Boundary

Active Learning (AL) requires learners to retrain the classifier with th...

0 Xiaofeng Cao, et al. ∙

research

∙ 01/30/2018

An Attention-Based Word-Level Interaction Model: Relation Detection for Knowledge Base Question Answering

Relation detection plays a crucial role in Knowledge Base Question Answe...

0 Hongzhi Zhang, et al. ∙

Guandong Xu

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