4 papers
Learning Invariant Visual Representations for Planning with Joint-Embedding Predictive World Models
Leonardo F. Toso, Davit Shadunts, Yunyang Lu +4
World models learned from high-dimensional visual observations allow agents to make decisions and plan directly in latent space, avoiding pixel-level reconstruction. However, recen…
SOCRATES: Simulation Optimization with Correlated Replicas and Adaptive Trajectory Evaluations
Haoting Zhang, Haoxian Chen, Donglin Zhan +5
The field of simulation optimization (SO) encompasses various methods developed to optimize complex, expensive-to-sample stochastic systems. Established methods include, but are no…
Collaborative Bayesian Optimization via Wasserstein Barycenters
Donglin Zhan, Haoting Zhang, Rhonda Righter +2
Motivated by the growing need for black-box optimization and data privacy, we introduce a collaborative Bayesian optimization (BO) framework that addresses both of these challenges…
Coreset-Based Task Selection for Sample-Efficient Meta-Reinforcement Learning
Donglin Zhan, Leonardo F. Toso, James Anderson
We study task selection to enhance sample efficiency in model-agnostic meta-reinforcement learning (MAML-RL). Traditional meta-RL typically assumes that all available tasks are equ…