Jian Pei

Secure and Efficient Skyline Queries on Encrypted Data

2018 · IEEE Transactions on Knowledge and Data Engineering

Outsourcing data and computation to cloud server provides a cost-effective way to support large scale data storage and query processing. However, due to security and privacy concerns, sensitive data (e.g., medical records) need to be …

Data Pricing and Data Asset Governance in the AI Era

2021

Data is one of the most critical resources in the AI Era. While substantial research has been dedicated to training machine learning models using various types of data, much less efforts have been invested in …

Knowledge-Enhanced Hierarchical Graph Transformer Network for Multi-Behavior Recommendation

2021 · Proceedings of the AAAI Conference on Artificial Intelligence

Accurate user and item embedding learning is crucial for modern recommender systems. However, most existing recommendation techniques have thus far focused on modeling users' preferences over singular type of user-item interactions. Many practical recommendation scenarios …

Graph Neural Networks: Foundation, Frontiers and Applications

2022 · Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

The field of graph neural networks (GNNs) has seen rapid and incredible strides over the recent years. Graph neural networks, also known as deep learning on graphs, graph representation learning, or geometric deep learning, have …

Graph Neural Networks for Natural Language Processing: A Survey

2023 · Foundations and Trends® in Machine Learning

Deep learning has become the dominant approach in addressing various tasks in Natural Language Processing (NLP). Although text inputs are typically represented as a sequence of tokens, there is a rich variety of NLP problems …

Disentangled Graph Social Recommendation

2023

Social recommender systems have drawn a lot of attention in many online web services, because of the incorporation of social information between users in improving recommendation results. Despite the significant progress made by existing solutions, …

Serverless Federated AUPRC Optimization for Multi-Party Collaborative Imbalanced Data Mining

2023 · arXiv (Cornell University)

Multi-party collaborative training, such as distributed learning and federated learning, is used to address the big data challenges. However, traditional multi-party collaborative training algorithms were mainly designed for balanced data mining tasks and are intended …

Protecting Data Buyer Privacy in Data Markets

2024 · arXiv (Cornell University)

Data markets serve as crucial platforms facilitating data discovery, exchange, sharing, and integration among data users and providers. However, the paramount concern of privacy has predominantly centered on protecting privacy of data owners and third …

Multiple Choice Questions based Multi-Interest Policy Learning for Conversational Recommendation

2022 · Proceedings of the ACM Web Conference 2022

Conversational recommendation system (CRS) is able to obtain fine-grained and dynamic user preferences based on interactive dialogue. Previous CRS assumes that the user has a clear target item, which often deviates from the real scenario, …