ICML Accepted

I’m very happy to announce that our paper “Fast and Consistent Learning of Hidden Markov Models by Incorporating Non-Consecutive Correlations” has been accepted for this year’s International Conference on Machine Learning (ICML’20).

This work has been developed in collaboration with Cristian Rojas, Eric Moulines, Vikram Krishnamurthy and Bo Wahlberg.

In the paper, we study how the parameters of an HMM can be estimated from observed data in fast and algorithmically attractive ways. The work could benefit practitioners working with large-scale time-series datasets (e.g., bioscience, finance, social networks, …).

A “preprint” of the paper is available in my PhD thesis (see Chapter 4) – to be defended tomorrow.