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A Regret Minimization Approach to Iterative Learning Control
We consider the setting of iterative learning control, or model-based po...
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Deluca – A Differentiable Control Library: Environments, Methods, and Benchmarking
We present an open-source library of natively differentiable physics and...
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PAC-BUS: Meta-Learning Bounds via PAC-Bayes and Uniform Stability
We are motivated by the problem of providing strong generalization guara...
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Generating Adversarial Disturbances for Controller Verification
We consider the problem of generating maximally adversarial disturbances...
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LagNetViP: A Lagrangian Neural Network for Video Prediction
The dominant paradigms for video prediction rely on opaque transition mo...
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Learning to Actively Reduce Memory Requirements for Robot Control Tasks
Robots equipped with rich sensing modalities (e.g., RGB-D cameras) perfo...
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Generalization Guarantees for Multi-Modal Imitation Learning
Control policies from imitation learning can often fail to generalize to...
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CoNES: Convex Natural Evolutionary Strategies
We present a novel algorithm – convex natural evolutionary strategies (C...
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Invariant Policy Optimization: Towards Stronger Generalization in Reinforcement Learning
A fundamental challenge in reinforcement learning is to learn policies t...
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Probably Approximately Correct Vision-Based Planning using Motion Primitives
This paper presents a deep reinforcement learning approach for synthesiz...
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Learning Task-Driven Control Policies via Information Bottlenecks
This paper presents a reinforcement learning approach to synthesizing ta...
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A Survey of Recent Scalability Improvements for Semidefinite Programming with Applications in Machine Learning, Control, and Robotics
Historically, scalability has been a major challenge to the successful a...
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Task-Driven Estimation and Control via Information Bottlenecks
Our goal is to develop a principled and general algorithmic framework fo...
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PAC-Bayes Control: Synthesizing Controllers that Provably Generalize to Novel Environments
Our goal is to synthesize controllers for robots that provably generaliz...
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Risk-sensitive Inverse Reinforcement Learning via Semi- and Non-Parametric Methods
The literature on Inverse Reinforcement Learning (IRL) typically assumes...
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How Should a Robot Assess Risk? Towards an Axiomatic Theory of Risk in Robotics
Endowing robots with the capability of assessing risk and making risk-aw...
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Response to "Counterexample to global convergence of DSOS and SDSOS hierarchies"
In a recent note [8], the author provides a counterexample to the global...
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DSOS and SDSOS Optimization: More Tractable Alternatives to Sum of Squares and Semidefinite Optimization
In recent years, optimization theory has been greatly impacted by the ad...
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Funnel Libraries for Real-Time Robust Feedback Motion Planning
We consider the problem of generating motion plans for a robot that are ...
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