2 papers
cs.NI2026
In-Network Market Prediction Using Machine Learning and Limit Order Books
Xinpeng Hong, Changgang Zheng, Joshua Lilley +2
Machine learning is significantly transforming algorithmic trading, yet the requirement for rapid execution speeds persists. While both aspects aim to boost profitability, embeddin…
cs.PF2025
Seeing is believing: The case for hardware-centric inefficiency detection and remediation
Ziji Chen, Steven W. D. Chien, Peng Qian +1
Large-scale machine learning workloads on the cloud suffer from silent inefficiencies, which do not trigger failures or obvious anomalies, making them hard to detect and diagnose.…