Ming Gao

Practical attacks on decoy-state quantum-key-distribution systems with detector efficiency mismatch

2015 · Physical Review A

To the active-basis-choice decoy-state quantum-key-distribution systems with detector efficiency mismatch, we present a modified attack strategy, which is based on the faked states attack, with quantum nondemolition measurement ability to restress the threat of detector …

An Improved Method for Named Entity Recognition and Its Application to CEMR

2019 · Future Internet

Named Entity Recognition (NER) on Clinical Electronic Medical Records (CEMR) is a fundamental step in extracting disease knowledge by identifying specific entity terms such as diseases, symptoms, etc. However, the state-of-the-art NER methods based on …

TransPrompt v2: Transferable Prompt-based Fine-tuning for Few-shot Text Classification

2022 · Research Square

Abstract Recent studies have shown that prompt-based fine-tuning improves the performance of large Pre-trained Language Models (PLMs) for few-shot text classification. Specifically, this type of method transforms the text classification task into the inherent Masked …

Knowledge Prompting in Pre-trained Language Model for Natural Language Understanding

2022 · arXiv (Cornell University)

Knowledge-enhanced Pre-trained Language Model (PLM) has recently received significant attention, which aims to incorporate factual knowledge into PLMs. However, most existing methods modify the internal structures of fixed types of PLMs by stacking complicated modules, …

GradMA: A Gradient-Memory-based Accelerated Federated Learning with Alleviated Catastrophic Forgetting

2023 · arXiv (Cornell University)

Federated Learning (FL) has emerged as a de facto machine learning area and received rapid increasing research interests from the community. However, catastrophic forgetting caused by data heterogeneity and partial participation poses distinctive challenges for …

UPFL: Unsupervised Personalized Federated Learning towards New Clients

2023 · arXiv (Cornell University)

Personalized federated learning has gained significant attention as a promising approach to address the challenge of data heterogeneity. In this paper, we address a relatively unexplored problem in federated learning. When a federated model has …

BiRank: Towards Ranking on Bipartite Graphs

2016 · IEEE Transactions on Knowledge and Data Engineering

The bipartite graph is a ubiquitous data structure that can model the relationship between two entity types: for instance, users and items, queries and webpages. In this paper, we study the problem of ranking vertices …