Carlee Joe‐Wong · PaperMetrix

Harnessing the Power of the Cloud: Revenue, Fairness, and Cloud Neutrality

2018 · Journal of Management Information Systems

Cloud computing is a transformational technology that reduces upfront infrastructure costs, democratizes access to computing and storage capacity, and helps businesses innovate and compete in the digital economy. However, the distribution of these significant social …

ECHO: Efficiently Overbooking Applications to Create a Highly Available Cloud

2019

Ensuring high availability for applications despite unpredictable cloud component failure events is a well-known problem in managing cloud infrastructure. One proposed solution uses a VM redundancy approach, reserving cloud resources for backup VMs that can …

FedRule: Federated Rule Recommendation System with Graph Neural Networks

2022 · arXiv (Cornell University)

Much of the value that IoT (Internet-of-Things) devices bring to ``smart'' homes lies in their ability to automatically trigger other devices' actions: for example, a smart camera triggering a smart lock to unlock a door. …

Adversarial Robustness Unhardening via Backdoor Attacks in Federated Learning

2023 · arXiv (Cornell University)

The delicate equilibrium between user privacy and the ability to unleash the potential of distributed data is an important concern. Federated learning, which enables the training of collaborative models without sharing of data, has emerged …

DYNAMITE: Dynamic Interplay of Mini-Batch Size and Aggregation Frequency for Federated Learning with Static and Streaming Dataset

2023 · arXiv (Cornell University)

Federated Learning (FL) is a distributed learning paradigm that can coordinate heterogeneous edge devices to perform model training without sharing private data. While prior works have focused on analyzing FL convergence with respect to hyperparameters …

HumekaFL: Automated Detection of Neonatal Asphyxia Using Federated Learning

2024 · arXiv (Cornell University)