Fei Chen

A Compressive Integrity Auditing Protocol for Secure Cloud Storage

2021 · IEEE/ACM Transactions on Networking

With the widespread application of cloud storage, ensuring the integrity of user outsourced data catches more and more attention. To remotely check the integrity of cloud storage, plenty of protocols have been proposed, implemented by …

LV-BERT: Exploiting Layer Variety for BERT

2021 · arXiv (Cornell University)

Modern pre-trained language models are mostly built upon backbones stacking self-attention and feed-forward layers in an interleaved order. In this paper, beyond this stereotyped layer pattern, we aim to improve pre-trained models by exploiting layer …

Convolutional dual graph Laplacian sparse coding

2022 · arXiv (Cornell University)

In recent years, graph signal processing (GSP) technology has become popular in various fields, and graph Laplacian regularizers have also been introduced into convolutional sparse representation. This paper proposes a convolutional sparse representation model based …

Application of Big Data Processing Technology in Power Marketing System

2022

Based on multi data fusion, this paper introduces a retrieval model for audio frequency data, which is combined with big data and applied to information retrieval. Firstly, the model is pre trained, and then the …

Efficient retrieval of power structured data with global data access view

2023

With the deepening of power grid informatization construction, the number of structured data such as equipment, network and operation data used in power system is increasing rapidly. In order to improve the efficiency of power …

VPFL: A Verifiable Property Federated Learning Framework Against Invisible Attacks in Distributed IoT

2023

The development of Federated Learning (FL) offers an efficient Machine Learning (ML) approach with privacy protection to solve the data island issue in distributed Internet of Things (IoT). However, existing FL frameworks still suffer from …

Human-Humanoid Robots Cross-Embodiment Behavior-Skill Transfer Using Decomposed Adversarial Learning from Demonstration

2024 · arXiv (Cornell University)

Humanoid robots are envisioned as embodied intelligent agents capable of performing a wide range of human-level loco-manipulation tasks, particularly in scenarios requiring strenuous and repetitive labor. However, learning these skills is challenging due to the …