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Found 6 papers, 0 papers with code
Skill Transfer and Discovery for Sim-to-Real Learning: A Representation-Based Viewpoint
Moreover, to handle the sim-to-real gap in the dynamics, we propose a skill discovery algorithm that learns new skills caused by the sim-to-real gap from real-world data.
TS-RSR: A provably efficient approach for batch bayesian optimization
This paper presents a new approach for batch Bayesian Optimization (BO) called Thompson Sampling-Regret to Sigma Ratio directed sampling (TS-RSR), where we sample a new batch of actions by minimizing a Thompson Sampling approximation of a regret to uncertainty ratio.
Stochastic Nonlinear Control via Finite-dimensional Spectral Dynamic Embedding
This paper presents an approach, Spectral Dynamics Embedding Control (SDEC), to optimal control for nonlinear stochastic systems.
FedDAR: Federated Domain-Aware Representation Learning
To make sure the FL model is robust when facing heterogeneous data among FL clients, most efforts focus on personalizing models for clients.
Gradient play in stochastic games: stationary points, convergence, and sample complexity
We show that Nash equilibria (NEs) and first-order stationary policies are equivalent in this setting, and give a local convergence rate around strict NEs.
LQR with Tracking: A Zeroth-order Approach and Its Global Convergence
In this work, we consider the general case where the target is allowed to be arbitrary, which we refer to as the LQR tracking problem.
