We introduce a new sequential importance sampling (SIS) algorithm which propagates in time a Monte Carlo approximation of the posterior fixed-lag smoothing distribution of the symb...
We propose a new unsupervised learning technique for extracting information about authors and topics from large text collections. We model documents as if they were generated by a...
Michal Rosen-Zvi, Chaitanya Chemudugunta, Thomas L...
This paper concerns learning and prediction with probabilistic models where the domain sizes of latent variables have no a priori upper-bound. Current approaches represent prior d...
Global mobile robot localization is the problem of determining a robot's pose in an environment, using sensor data, when the starting position is unknown. A family of probabi...
With technology scaling down to 90nm and below, many yield-driven design and optimization methodologies have been proposed to cope with the prominent process variation and to incr...
Fang Gong, Hao Yu, Yiyu Shi, Daesoo Kim, Junyan Re...