Li Pan

DRL-Scheduling: An Intelligent QoS-Aware Job Scheduling Framework for Applications in Clouds

2018 · IEEE Access

As an increasing number of traditional applications migrated to the cloud, achieving resource management and performance optimization in such a dynamic and uncertain environment becomes a big challenge for cloud-based application providers. In particular, job …

Paper Recommendation Based on Author-paper Interest and Graph Structure

2021

The recommendation system can recommend information to users efficaciously, which helps many users to obtain information in different fields. The paper recommendation is a research topic to provide authors with personalized papers of interest. However, …

Attribute Augmented Network Embedding Based on Generative Adversarial Nets

2021 · IEEE Transactions on Neural Networks and Learning Systems

Network embedding is to learn low-dimensional representations of nodes while preserving necessary information for network analysis tasks. Though representations preserving both structure and attribute features have achieved in many real-world applications, learning these representations for …

A Benchmark on Directed Graph Representation Learning in Hardware Designs

2024 · arXiv (Cornell University)

To keep pace with the rapid advancements in design complexity within modern computing systems, directed graph representation learning (DGRL) has become crucial, particularly for encoding circuit netlists, computational graphs, and developing surrogate models for hardware …

Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning

2024 · arXiv (Cornell University)

Large Language Models (LLMs) embed sensitive, human-generated data, prompting the need for unlearning methods. Although certified unlearning offers strong privacy guarantees, its restrictive assumptions make it unsuitable for LLMs, giving rise to various heuristic approaches …