In this paper we describe a model of the process by which people solve problems using information visualization systems. The model was based on video analysis of forty dyads who p...
Continuous state spaces and stochastic, switching dynamics characterize a number of rich, realworld domains, such as robot navigation across varying terrain. We describe a reinfor...
Emma Brunskill, Bethany R. Leffler, Lihong Li, Mic...
Gaussian graphical models are of great interest in statistical learning. Because the conditional independencies between different nodes correspond to zero entries in the inverse c...
We present a distributed machine learning framework based on support vector machines that allows classification problems to be solved iteratively through parallel update algorithm...
This paper solves the variation-aware on-chip decoupling capacitance (decap) budgeting problem. Unlike previous work assuming the worst-case current load, we develop a novel stocha...