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09/29/2021
Vitruvion: A Generative Model of Parametric CAD Sketches
Parametric computer-aided design (CAD) tools are the predominant way tha...
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07/31/2021
Compressed sensing in the presence of speckle noise
The problem of recovering a structured signal from its linear measuremen...
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03/02/2021
Autobahn: Automorphism-based Graph Neural Nets
We introduce Automorphism-based graph neural networks (Autobahn), a new ...
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07/16/2020
SketchGraphs: A Large-Scale Dataset for Modeling Relational Geometry in Computer-Aided Design
Parametric computer-aided design (CAD) is the dominant paradigm in mecha...
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03/03/2020
Error bounds in estimating the out-of-sample prediction error using leave-one-out cross validation in high-dimensions
We study the problem of out-of-sample risk estimation in the high dimens...
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01/29/2020
Asymptotics of Cross-Validation
Cross validation is a central tool in evaluating the performance of mach...
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07/18/2019
Discrete Object Generation with Reversible Inductive Construction
The success of generative modeling in continuous domains has led to a su...
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01/17/2019
Denoising of structured random processes
Denoising stationary process (X_i)_i ∈ Z corrupted by additive white Gau...
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10/04/2018
Approximate Leave-One-Out for High-Dimensional Non-Differentiable Learning Problems
Consider the following class of learning schemes: β̂ := β∈C ∑_j=1^n ℓ(x_...
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07/07/2018
Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions
Consider the following class of learning schemes: β̂ := _β ∑_j=1^n ℓ(x_j...
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06/27/2018
Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data
Empirical risk minimization is the principal tool for prediction problem...
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04/16/2018