Latest Publications

New publications

Spectral norm bounds for block Markov chain random matrices

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We have submitted Spectral norm bounds for block Markov chain random matrices, and it is currently under review. This is joint work between Albert Senen-Cerda and myself. A preprint is available on arXiv.

Universal Approximation in Dropout Neural Networks

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Dropout and Dropconnect on a shallow neural network

Asymptotic convergence rate of Dropout on shallow linear neural networks

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Modeling Rydberg Gases using Random Sequential Adsorption on Random Graphs

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Example random neural network when using Dropconnect

Almost Sure Convergence of Dropout Algorithms for Neural Networks

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Latest News

Conference

XVII Brunel-Bielefeld Workshop

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Today, Albert Senen-Cerda and Alexander Van Werde presented two posters at the XVII Brunel-Bielefeld Workshop on Random Matrix Theory and Applications.

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Review

Eigenvalue rigidity for truncations of random unitary matrices

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Here is a public review of “Eigenvalue rigidity for truncations of random unitary matrices,” which I recently wrote for Mathematical Reviews.

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Reinforcement Learning in Block Markov Chains

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ICML 2020

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article arxiv asymptotics Block Markov Chains clustering Markov chain mathematics networks physics probability theory
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