A novel framework of compressed sensing, namely statistical compressed sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical distribu...
Many problems in computer vision can be modeled using
conditional Markov random fields (CRF). Since finding
the maximum a posteriori (MAP) solution in such models
is NP-hard, mu...
Stephen Gould (Stanford University), Fernando Amat...
We present a probabilistic framework for recognizing objects in images of cluttered scenes. Hundreds of objects may be considered and searched in parallel. Each object is learned f...
Frameworks promote design and code reuse, at a higher level of granularity. The use of frameworks is a hard task though, because usually they lack documentation and instructions o...
Subtle implementation errors or mis-configurations in complex Internet services may lead to performance degradations without causing failures. These undiscovered performance anomal...
Christopher Stewart, Kai Shen, Arun Iyengar, Jian ...