New publications Archives

Universal Approximation in Dropout Neural Networks

We have submitted Universal Approximation in Dropout Neural Networks, and it is currently under review. This is joint work between, Oxana Manita, Mark Peletier, Jacobus Portegies, Albert Senen-Cerda and myself. A preprint is available on arXiv.

Dropout and Dropconnect on a shallow neural network

New publications

Asymptotic convergence rate of Dropout on shallow linear neural networks

We have submitted Asymptotic convergence rate of Dropout on shallow linear neural networks, and it is currently under review. This is joint work between Albert Senen-Cerda and myself. A preprint is available on arXiv.

New publications

Modeling Rydberg Gases using Random Sequential Adsorption on Random Graphs

We have submitted “Modeling Rydberg Gases using Random Sequential Adsorption on Random Graphs.” This is joint work with Daan Rutten.

Example random neural network when using Dropconnect

New publications

Almost Sure Convergence of Dropout Algorithms for Neural Networks

We have submitted Almost Sure Convergence of Dropout Algorithms for Neural Networks, and it is currently under review. This is joint work between Albert Senen-Cerda and myself.

Schematic depiction of the hitting time for the Schatten p norm

New publications

Markov chains for error accumulation in quantum circuits

We have submitted Markov chains for error accumulation in quantum circuits, and it is currently under review. This is joint work between Long Ma and myself. A preprint is available on arXiv.

New publications

Optimal clustering algorithms in Block Markov Chains

We have submitted Optimal Clustering Algorithms in Block Markov Chains, and it is currently under review. This is joint work between myself and Alexandre Proutiere. A preprint is available on arXiv.

New publications

Scaling limits and generic bounds for exploration processes

We have submitted Scaling limits and generic bounds for exploration processes, and it is currently under review. It is joint work between Paola Bermolen, Matthieu Jonckheere, and Jaron Sanders. A preprint is available on arXiv.

New publications

Optimality gaps in asymptotic dimensioning of many-server systems

We have submitted Optimality gaps in asymptotic dimensioning of many-server systems, and it is currently under review. This is joint work between Jaron Sanders, Sem Borst, Johan van Leeuwaarden, and Guido Janssen. The arXiv preprint can be obtained via this link.

New publications

Universal Approximation in Dropout Neural Networks

Asymptotic convergence rate of Dropout on shallow linear neural networks

Modeling Rydberg Gases using Random Sequential Adsorption on Random Graphs

Almost Sure Convergence of Dropout Algorithms for Neural Networks

Markov chains for error accumulation in quantum circuits

Optimal clustering algorithms in Block Markov Chains

Scaling limits and generic bounds for exploration processes

Optimality gaps in asymptotic dimensioning of many-server systems

Contact details

Visit / Postal address