Background: High throughput sequencing has become an important technology for studying expression levels in many types of genomic, and particularly transcriptomic, data. One key w...
Learning Bayesian networks from data is an N-P hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational comple...
In this paper, we present an unsupervised method for mining activities in videos. From unlabeled video sequences of a scene, our method can automatically recover what are the recu...
Ré, mi Emonet, Jagannadan Varadarajan, Jean-Marc ...
—Understanding the communication behavior and network resource usage of parallel applications is critical to achieving high performance and scalability on systems with tens of th...
Ron Brightwell, Kevin T. Pedretti, Kurt B. Ferreir...
We develop new techniques for time series classification based on hierarchical Bayesian generative models (called mixed-effect models) and the Fisher kernel derived from them. A k...