10 citations · 10 across the 4 of their papers we have counts for
4 papers · 1 filter
Exploring Silent Data Corruption as a Reliability Challenge in LLM Training
Anton Altenbernd, Philipp Wiesner, Odej Kao
As Large Language Models (LLMs) scale in size and complexity, the consequences of failures during training become increasingly severe. A major challenge arises from Silent Data Cor…
-GNN: A Robust Ensemble Approach Against Graph Structure Perturbation
Haci Ismail Aslan, Philipp Wiesner, Ping Xiong +1
Graph Neural Networks (GNNs) are playing an increasingly important role in the efficient operation and security of computing systems, with applications in workload scheduling, anom…
Federated Learning over Connected Modes
Dennis Grinwald, Philipp Wiesner, Shinichi Nakajima
Statistical heterogeneity in federated learning poses two major challenges: slow global training due to conflicting gradient signals, and the need of personalization for local dist…
LogRCA: Log-based Root Cause Analysis for Distributed Services
Thorsten Wittkopp, Philipp Wiesner, Odej Kao
To assist IT service developers and operators in managing their increasingly complex service landscapes, there is a growing effort to leverage artificial intelligence in operations…