1 citations · 2 across the 8 of their papers we have counts for
4 papers · 1 filter
Learned Neighbor Trust for Collaborative Deployment in Model-Agnostic Decentralized Learning
Michael Lanier, Luise Ge, Sastry Kompella +1
Many decentralized distillation methods are designed around training-time coordination, yet deploy each node in isolation even when more capable neighbors remain available at infer…
A Scalable Approach to Solving Simulation-Based Network Security Games
Michael Lanier, Yevgeniy Vorobeychik
We introduce MetaDOAR, a lightweight meta-controller that augments the Double Oracle / PSRO paradigm with a learned, partition-aware filtering layer and Q-value caching to enable s…
Learning Policy Committees for Effective Personalization in MDPs with Diverse Tasks
Luise Ge, Michael Lanier, Anindya Sarkar +3
Many dynamic decision problems, such as robotic control, involve a series of tasks, many of which are unknown at training time. Typical approaches for these problems, such as multi…
Learning Interpretable Policies in Hindsight-Observable POMDPs through Partially Supervised Reinforcement Learning
Michael Lanier, Ying Xu, Nathan Jacobs +2
Deep reinforcement learning has demonstrated remarkable achievements across diverse domains such as video games, robotic control, autonomous driving, and drug discovery. Common met…