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06/16/2023
Gradient is All You Need?
In this paper we provide a novel analytical perspective on the theoretic...
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11/08/2022
Finite Sample Identification of Wide Shallow Neural Networks with Biases
Artificial neural networks are functions depending on a finite number of...
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08/22/2022
Semi-Supervised Manifold Learning with Complexity Decoupled Chart Autoencoders
Autoencoding is a popular method in representation learning. Conventiona...
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11/15/2021
Convergence of Anisotropic Consensus-Based Optimization in Mean-Field Law
In this paper we study anisotropic consensus-based optimization (CBO), a...
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10/29/2021
Landscape analysis of an improved power method for tensor decomposition
In this work, we consider the optimization formulation for symmetric ten...
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03/28/2021
Consensus-based optimization methods converge globally in mean-field law
In this paper we study consensus-based optimization (CBO), which is a mu...
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01/18/2021
Stable Recovery of Entangled Weights: Towards Robust Identification of Deep Neural Networks from Minimal Samples
In this paper we approach the problem of unique and stable identifiabili...
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08/06/2020
ReLU nets adapt to intrinsic dimensionality beyond the target domain
We study the approximation of two-layer compositions f(x) = g(ϕ(x)) via ...
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03/10/2020
Estimating multi-index models with response-conditional least squares
The multi-index model is a simple yet powerful high-dimensional regressi...
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09/26/2019
Estimating covariance and precision matrices along subspaces
We study the accuracy of estimating the covariance and the precision mat...
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06/30/2019
Robust and Resource Efficient Identification of Two Hidden Layer Neural Networks
We address the structure identification and the uniform approximation of...
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02/24/2019
Nonlinear generalization of the single index model
Single index model is a powerful yet simple model, widely used in statis...
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10/11/2017
