Recovered transition matrix of a Block Markov Chain

ML Seminars: Clustering in Block Markov Chains

After presenting my poster at Stochastic Networks 2018 on our manuscript Optimal Clustering Algorithms in Block Markov Chains, I received an invitation to give a presentation at the machine learning seminar of the machine learning research group at the Centrum Wiskunde & Informatica in Amsterdam, The Netherlands. Not long thereafter, our own Algorithmics Group here at TU Delft also extended another invitation to present at their machine learning seminar. My co-author Alexandre Proutière also received an invitation to present our work on clustering in block Markov chains at the 56th Annual Allerton Conference on Communication, Control and Computing.

Our revised manuscript

Around the same time, we also received feedback on our manuscript that was (and still is) under submission. The feedback gave us new ideas on how to tighten our results, and together with the help of Se Young Yun, we succesfully extended our proofs to allow for substantially improved results. Our revision, together with our improved results, are now available on arXiv:

Clustering in Block Markov Chains (2018), by Jaron Sanders, Alexandre Proutière, and Se-Young Yun. Manuscript under submission, a preprint is available on arXiv here.

My presentation

I therefore decided to cover our new results in these presentations. I gave my presentation the same new title as our revised manuscript, Clustering in Block Markov Chains. Furthermore, I designed it as a sneak preview into what we would soon upload to arXiv – as I incorporated our latest results from the revision that we were finishing. Here is the presentation:

Jaron Sanders received in 2012 M.Sc. degrees in Mathematics and Physics from the Eindhoven University of Technology, The Netherlands, as well as a PhD degree in Mathematics in 2016. After he obtained his PhD degree, he worked as a post-doctoral researcher at the KTH Royal Institute of Technology in Stockholm, Sweden. Jaron Sanders then worked as an assistant professor at the Delft University of Technology, and now works as an assistant professor at the Eindhoven University of Technology. His research interests are applied probability, queueing theory, stochastic optimization, stochastic networks, wireless networks, and interacting (particle) systems.