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ICML
2007
IEEE
16 years 5 months ago
Unsupervised estimation for noisy-channel models
Shannon's Noisy-Channel model, which describes how a corrupted message might be reconstructed, has been the corner stone for much work in statistical language and speech proc...
Markos Mylonakis, Khalil Sima'an, Rebecca Hwa
ICML
2006
IEEE
16 years 5 months ago
A choice model with infinitely many latent features
Elimination by aspects (EBA) is a probabilistic choice model describing how humans decide between several options. The options from which the choice is made are characterized by b...
Carl Edward Rasmussen, Dilan Görür, Fran...
ICML
2000
IEEE
16 years 5 months ago
Maximum Entropy Markov Models for Information Extraction and Segmentation
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
DSN
2008
IEEE
15 years 11 months ago
A recurrence-relation-based reward model for performability evaluation of embedded systems
Embedded systems for closed-loop applications often behave as discrete-time semi-Markov processes (DTSMPs). Performability measures most meaningful to iterative embedded systems, ...
Ann T. Tai, Kam S. Tso, William H. Sanders
CVPR
2006
IEEE
15 years 11 months ago
Depth from Familiar Objects: A Hierarchical Model for 3D Scenes
We develop an integrated, probabilistic model for the appearance and three-dimensional geometry of cluttered scenes. Object categories are modeled via distributions over the 3D lo...
Erik B. Sudderth, Antonio B. Torralba, William T. ...