5 papers
DOPPLER: Dual-Policy Learning for Device Assignment in Asynchronous Dataflow Graphs
Xinyu Yao, Daniel Bourgeois, Abhinav Jain +5
We study the problem of assigning operations in a dataflow graph to devices to minimize execution time in a work-conserving system, with emphasis on complex machine learning worklo…
Cross-Domain Graph Anomaly Detection via Test-Time Training with Homophily-Guided Self-Supervision
Delaram Pirhayati, Arlei Silva
Graph Anomaly Detection (GAD) has demonstrated great effectiveness in identifying unusual patterns within graph-structured data. However, while labeled anomalies are often scarce i…
How Millions Coordinate at Scale: Engagement, Collaboration, and Conflict in Three Editions of Reddit r/place
Yutong Wu, Arlei Silva
Mass peer-production environments are shaped by a complex interplay between decentralized coordination, platform design, and potential conflict over resources. While online infrast…
Sensor Placement for Learning in Flow Networks
Arnav Burudgunte, Arlei Silva
Large infrastructure networks (e.g. for transportation and power distribution) require constant monitoring for failures, congestion, and other adversarial events. However, assignin…
Fair Graph Machine Learning under Adversarial Missingness Processes
Debolina Halder Lina, Arlei Silva
Graph Neural Networks (GNNs) have achieved state-of-the-art results in many relevant tasks where decisions might disproportionately impact specific communities. However, existing w…