Causal Knowledge-Empowered Adaptive Federated Learning

Strength-Adaptive Adversarial Training

C Yu, D Zhou, L Shen, J Yu, B Han, M Gong, N Wang, T Liu

2026-09-01

Adversarial training (AT) has been shown to effectively enhance a network's resilience against adversarial attack. However, conven..

Observationally Informed Adaptive Causal Experimental Design

Erdun Gao, Liang Zhang, Jake Fawkes, Aoqi Zuo, Wenqin Liu, Haoxuan Li, Mingming Gong, Dino Sejdinovic

2026-08-09

Randomized Controlled Trials (RCTs) represent the gold standard for causal inference yet remain a scarce resource. While large-sca..

A joint time and energy-efficient federated learning-based computation offloading method for mobile edge computing

A Mukherjee, R Buyya

2026-05-01

Computation offloading at lower time and lower energy consumption is crucial for resource-constrained mobile devices. This paper p..

EnFed: An Energy-Aware Federated Learning in Resource Constrained Environments for Human Activity Recognition

A Mukherjee, R Buyya

2026-05-01

The human activity recognition (HAR) and recommendation applications for mobile users require a privacy-aware and accurate data an..

Evidential Trust-Aware Model Personalization in Decentralized Federated Learning for Wearable IoT

M Rangwala, RO Sinnott, R Buyya

2026-01-01

Decentralized federated learning (DFL) enables collaborative model training across edge devices without centralized coordination, ..

TraDE: Network and Traffic-Aware Adaptive Scheduling for Microservices Under Dynamics

M Chen, MT Islam, MR Read, R Buyya

2026-01-01

The transition from monolithic architecture to microservices has enhanced flexibility in application design and its scalable execu..

Debiased Recommendation via Wasserstein Causal Balancing

H Wang, Z Chen, H Zhang, Z Li, L Pan, H Li, M Gong

2025-09-12

Recommendation systems are pivotal in improving user experience on various digital platforms. However, observational training data..

Federated Learning Architectures: A Performance Evaluation With Crop Yield Prediction Application

A Mukherjee, R Buyya

2025-07-01

Introduction: Federated learning has become an emerging technology in data analysis for IoT applications. Methods: This paper impl..

A Two-Stage Pretraining-Finetuning Framework for Treatment Effect Estimation with Unmeasured Confounding

C Zhou, Y Li, C Zheng, H Zhang, M Zhang, H Li, M Gong

2025-01-01

Estimating the conditional average treatment effect (CATE) from observational data plays a crucial role in areas such as e-commerc..

Serv-Drishti: An Interactive Serverless Function Request Simulation Engine and Visualiser

Siddharth Agarwal, Maria A Rodriguez, Rajkumar Buyya

2025-01-01

The rapid adoption of serverless computing necessitates a deeper understanding of its underlying operational mechanics, particular..