Markov random field (MRF, CRF) models are popular in
computer vision. However, in order to be computationally
tractable they are limited to incorporate only local interactions
a...
Scientific and intelligence applications have special data handling needs. In these settings, data does not fit the standard model of short coded records that had dominated the dat...
There is increasing interest within the research community in the design and use of recursive probability models. There remains concern about computational complexity costs and th...
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
In this paper, we study a novel problem Collective Active Learning, in which we aim to select a batch set of "informative" instances from a networking data set to query ...