In this thesis, we present algorithms to model and identify shared patterns in human activity with respect to three applications. First, we propose a novel model to characterize the bursty dynamics found in human activity. ...

In this thesis, we study the computational and statistical aspects of several sparse models when the number of samples and/or features is large. We propose new statistical estimators and build new computational algorithms ...

We present our work with a hotel company as an example of how machine learning techniques can be used to improve the demand predictions of a hotel property, as well as its pricing and capacity allocation decisions. First, ...