137 citations · 713 across the 43 of their papers we have counts for
47 papers
Learning Fractional-Order Dynamics from a Single Trajectory
Xiaole Zhang, Ziyi Zhang, Zehao Zhao +4
Many real-world processes exhibit long-range dependence, where the current state depends on a slowly decaying trace of past states rather than on the most recent state alone. This…
CLT-Optimal Parameter Error Bounds for Linear System Identification
Yichen Zhou, Stephen Tu
There has been remarkable progress over the past decade in establishing finite-sample, non-asymptotic bounds on recovering unknown system parameters from observed system behavior.…
Robots That Ask For Help: Uncertainty Alignment for Large Language Model Planners
Allen Z. Ren, Anushri Dixit, Alexandra Bodrova +11
Large language models (LLMs) exhibit a wide range of promising capabilities -- from step-by-step planning to commonsense reasoning -- that may provide utility for robots, but remai…
Bootstrapped Representations in Reinforcement Learning
Charline Le Lan, Stephen Tu, Mark Rowland +4
In reinforcement learning (RL), state representations are key to dealing with large or continuous state spaces. While one of the promises of deep learning algorithms is to automati…
Agile Catching with Whole-Body MPC and Blackbox Policy Learning
Saminda Abeyruwan, Alex Bewley, Nicholas M. Boffi +9
We address a benchmark task in agile robotics: catching objects thrown at high-speed. This is a challenging task that involves tracking, intercepting, and cradling a thrown object…
The Power of Learned Locally Linear Models for Nonlinear Policy Optimization
Daniel Pfrommer, Max Simchowitz, Tyler Westenbroek +2
A common pipeline in learning-based control is to iteratively estimate a model of system dynamics, and apply a trajectory optimization algorithm - e.g.~ - on the lea…