Classical dynamic Bayesian networks (DBNs) are based on the homogeneous Markov assumption and cannot deal with heterogeneity and non-stationarity in temporal processes. Various ap...
In this paper we propose a new approach for semi-supervised structured output learning. Our approach uses relaxed labeling on unlabeled data to deal with the combinatorial nature ...
Paramveer S. Dhillon, S. Sathiya Keerthi, Kedar Be...
Data races are one of the most common and subtle causes of pernicious concurrency bugs. Static techniques for preventing data races are overly conservative and do not scale well t...
Daniel Marino, Madanlal Musuvathi, Satish Narayana...
We propose a shape population metric that reflects the interdependencies between points observed in a set of examples. It provides a notion of topology for shape and appearance m...
This paper suggests using discrete feature displacements and optical flow simultaneously to determine the camera motion and its velocity. This is advantageous when the number of ...