Gang Chen

Divide and conquer

2020

The multi-cloud composite applications deployment problem (MCADP) aims to select proper cloud resources from multiple cloud providers at different locations to deploy applications with shared constituent services in order to optimize performance and cost. In …

Achieving IoT Devices Secure Sharing in Multi-User Smart Space

2020

Multiple users often share their Internet of Things (IoT) devices in a smart space. However, existing IoT systems do not support IoT sharing between multiple users or take into account the security risks associated with …

Load Balancing in a Distributed Network Environment - An ACO Inspired Approach

2015

Abstract - The success of nature inspired algorithms, particularly Ant Colony Optimization (ACO) on various optimization and scheduling problems has inspired to apply this approach on load balancing problem. Messor is one such approach based …

A Comparative Study of in-Database Inference Approaches

2022 · 2022 IEEE 38th International Conference on Data Engineering (ICDE)

In Alibaba's IoT platform, we face the challenge of processing analytical queries involving both structured and unstructured data. Normally, collaborative queries need deep learning (DL) models and relational algebras to work intertwined to produce sophisticated …

Byzantine-Robust Learning on Heterogeneous Data via Gradient Splitting

2023 · arXiv (Cornell University)

Federated learning has exhibited vulnerabilities to Byzantine attacks, where the Byzantine attackers can send arbitrary gradients to a central server to destroy the convergence and performance of the global model. A wealth of robust AGgregation …

Assessing Hidden Risks of LLMs: An Empirical Study on Robustness, Consistency, and Credibility

2023 · arXiv (Cornell University)

The recent popularity of large language models (LLMs) has brought a significant impact to boundless fields, particularly through their open-ended ecosystem such as the APIs, open-sourced models, and plugins. However, with their widespread deployment, there …

ProMix: Combating Label Noise via Maximizing Clean Sample Utility

2023

Learning with Noisy Labels (LNL) has become an appealing topic, as imperfectly annotated data are relatively cheaper to obtain. Recent state-of-the-art approaches employ specific selection mechanisms to separate clean and noisy samples and then apply …

PV power prediction method based on ground-based cloud map and hybrid neural network

2023

Under cloudy weather, PV power will fluctuate dramatic due to the sporty cloud shading. However, most existing PV power prediction models do not utilize the cloud map sufficiently. In this paper, we propose a novel …

Quantum computation based on capture-and-release dynamics

2025 · Physical Review A

High-fidelity and decoherence-insensitive quantum gates are essential for achieving universal quantum computing. In quantum information processing, decoherence arising from excited states significantly contributes to the scheme's infidelity. Therefore, minimizing the average population of the excited …

Analysis and Research of Several Problems of Bad Short Message Filtering System

2015 · Advances in computer science research

the spread of bad message seriously affects the social ethos and disrupt the normal life order of people. It has considerable practical value to research and develop the filtering technology of bad short message. Two …

Personal recommendation using deep recurrent neural networks in NetEase

2016

Each user session in an e-commerce system can be modeled as a sequence of web pages, indicating how the user interacts with the system and makes his/her purchase. A typical recommendation approach, e.g., Collaborative Filtering, …