6 papers
Learning Not to Optimize: Physics-Informed Action-Space Reshaping for Intent-Based Network Control
Zuyuan Zhang, Vaneet Aggarwal, Tian Lan
Modern network policy control maps intent to sequential placement-control decisions. Bellman-style policy optimization primarily asks which action to optimize, while constraints ar…
Hierarchical Deep Counterfactual Regret Minimization
Jiayu Chen, Zhekai Wang, Vaneet Aggarwal
Imperfect Information Games (IIGs) offer robust models for scenarios where decision-makers face uncertainty or lack complete information. Counterfactual Regret Minimization (CFR) h…
Variational Offline Multi-agent Skill Discovery
Jiayu Chen, Tian Lan, Vaneet Aggarwal
Skills are effective temporal abstractions established for sequential decision making, which enable efficient hierarchical learning for long-horizon tasks and facilitate multi-task…
Rack Position Optimization in Large-Scale Heterogeneous Data Centers
Chang-Lin Chen, Jiayu Chen, Tian Lan +3
As rapidly growing AI computational demands accelerate the need for new hardware installation and maintenance, this work explores optimal data center resource management by balanci…
Network Diffuser for Placing-Scheduling Service Function Chains with Inverse Demonstration
Zuyuan Zhang, Vaneet Aggarwal, Tian Lan
Network services are increasingly managed by considering chained-up virtual network functions and relevant traffic flows, known as the Service Function Chains (SFCs). To deal with…
Learning-based Two-tiered Online Optimization of Region-wide Datacenter Resource Allocation
Chang-Lin Chen, Hanhan Zhou, Jiayu Chen +8
Online optimization of resource management for large-scale data centers and infrastructures to meet dynamic capacity reservation demands and various practical constraints (e.g., fe…