Motivated by theoretical advancements in dimensionality reduction techniques we use a recent model, called Block Markov Chains, to conduct a practical study of clustering in real-world sequential data.
Read more
New publications
Singular value distribution of dense random matrices with block Markovian dependence
We have submitted Singular value distribution of dense random matrices with block Markovian dependence, and it is currently under review. This is joint work between Alexander Van Werde and myself. A preprint is available on arXiv.
Read more
Spectral norm bounds for block Markov chain random matrices
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.
Read more
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.
Read more
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.
Read more
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.
Read more
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.
Read more