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20072023
most citedPractical Bayesian Optimization of Machine Learning Algorithms

5.7k citations · 15.5k across the 75 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

cs.LG2021★ 2 cited

ProBF: Learning Probabilistic Safety Certificates with Barrier Functions

Athindran Ramesh Kumar, Sulin Liu, Jaime F. Fisac +2

Safety-critical applications require controllers/policies that can guarantee safety with high confidence. The control barrier function is a useful tool to guarantee safety if we ha…

cs.LG2021★ 1 cited

Vitruvion: A Generative Model of Parametric CAD Sketches

Ari Seff, Wenda Zhou, Nick Richardson +1

Parametric computer-aided design (CAD) tools are the predominant way that engineers specify physical structures, from bicycle pedals to airplanes to printed circuit boards. The key…

cs.LG2021★ 10 cited

Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability

Dibya Ghosh, Jad Rahme, Aviral Kumar +3

Generalization is a central challenge for the deployment of reinforcement learning (RL) systems in the real world. In this paper, we show that the sequential structure of the RL pr…

cs.LG2021★ 1 cited

Amortized Synthesis of Constrained Configurations Using a Differentiable Surrogate

Xingyuan Sun, Tianju Xue, Szymon Rusinkiewicz +1

In design, fabrication, and control problems, we are often faced with the task of synthesis, in which we must generate an object or configuration that satisfies a set of constraint…

stat.ML2021★ 2 cited

Active multi-fidelity Bayesian online changepoint detection

Gregory W. Gundersen, Diana Cai, Chuteng Zhou +2

Online algorithms for detecting changepoints, or abrupt shifts in the behavior of a time series, are often deployed with limited resources, e.g., to edge computing settings such as…