Peilin Zhao

Learning User Dependencies for Recommendation

2017

Social recommender systems exploit users' social relationships to improve recommendation accuracy. Intuitively, a user tends to trust different people regarding with different scenarios. Therefore, one main challenge of social recommendation is to exploit the most …

Online Adaptive Asymmetric Active Learning with Limited Budgets

2019 · arXiv (Cornell University)

Online Active Learning (OAL) aims to manage unlabeled datastream by selectively querying the label of data. OAL is applicable to many real-world problems, such as anomaly detection in health-care and finance. In these problems, there …

Adaptive cost-sensitive online classification

2019 · Singapore Management University Institutional Knowledge (InK) (Singapore Management University)

National Research Foundation (NRF) Singapore under International Research Centres in Singapore Funding Initiative

$p$-Laplacian Based Graph Neural Networks

2021 · arXiv (Cornell University)

Graph neural networks (GNNs) have demonstrated superior performance for semi-supervised node classification on graphs, as a result of their ability to exploit node features and topological information simultaneously. However, most GNNs implicitly assume that the …

LLM-Based Agent Society Investigation: Collaboration and Confrontation in Avalon Gameplay

2023 · arXiv (Cornell University)

This paper explores the open research problem of understanding the social behaviors of LLM-based agents. Using Avalon as a testbed, we employ system prompts to guide LLM agents in gameplay. While previous studies have touched …

Variational Bayes for Federated Continual Learning

2024 · arXiv (Cornell University)

Federated continual learning (FCL) has received increasing attention due to its potential in handling real-world streaming data, characterized by evolving data distributions and varying client classes over time. The constraints of storage limitations and privacy …

Online Parallel Multi-Task Relationship Learning via Alternating Direction Method of Multipliers

2024 · arXiv (Cornell University)

Online multi-task learning (OMTL) enhances streaming data processing by leveraging the inherent relations among multiple tasks. It can be described as an optimization problem in which a single loss function is defined for multiple tasks. …

Privacy Preserving Point-of-Interest Recommendation Using Decentralized Matrix Factorization

2018 · Proceedings of the AAAI Conference on Artificial Intelligence

Points of interest (POI) recommendation has been drawn much attention recently due to the increasing popularity of location-based networks, e.g., Foursquare and Yelp. Among the existing approaches to POI recommendation, Matrix Factorization (MF) based techniques …