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...
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
We investigate techniques for analysis and retrieval of object trajectories in a two or three dimensional space. Such kind of data usually contain a great amount of noise, that ma...
Michail Vlachos, Dimitrios Gunopulos, George Kolli...
Given a classification problem, our goal is to find a low-dimensional linear transformation of the feature vectors which retains information needed to predict the class labels. We...
Production systems are commonly plagued by intermittent problems that are difficult to diagnose. This paper describes a new diagnostic tool, called Chopstix, that continuously col...
Sapan Bhatia, Abhishek Kumar, Marc E. Fiuczynski, ...