We consider a semi-supervised regression setting where we have temporal sequences of partially labeled data, under the assumption that the labels should vary slowly along a sequen...
In this work we address the problem of modeling varying time duration sequences for large-scale human routine discovery from cellphone sensor data using a multi-level approach to p...
This paper concerns the fundamental problem of identifying the content nature of a flow, namely text, binary, or encrypted, for the first time. We propose Iustitia, a tool for ide...
In this paper, we present an approach to monitor human activities such as entry, exit and break times of people in a workplace environment. The companion robot then learns the use...
Amol A. Deshmukh, Mei Yii Lim, Michael Kriegel, Ru...
We present SpeedBoost, a natural extension of functional gradient descent, for learning anytime predictors, which automatically trade computation time for predictive accuracy by s...