We focus on the problem of selecting the few vehicles in a fleet that are expected to last the longest without failure. The prediction of each vehicle’s remaining life is based o...
In probabilistic grammatical inference, a usual goal is to infer a good approximation of an unknown distribution P called a stochastic language. The estimate of P stands in some cl...
This work presents a study to bridge topic modeling and personalized search. A probabilistic topic model is used to extract topics from user search history. These topics can be se...
—This paper studies the blocking performance of a class of all-optical overlaid-star TDM networks using a leastcongested-path routing strategy for path selection. An analytical m...
We present an image-based approach to infer 3D structure parameters using a probabilistic "shape+structure" model. The 3D shape of an object class is represented by sets...
Kristen Grauman, Gregory Shakhnarovich, Trevor Dar...