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CVPR
2009
IEEE
17 years 2 months ago
Learning Optimized MAP Estimates in Continuously-Valued MRF Models
We present a new approach for the discriminative training of continuous-valued Markov Random Field (MRF) model parameters. In our approach we train the MRF model by optimizing t...
Kegan G. G. Samuel, Marshall F. Tappen
CVPR
2003
IEEE
16 years 9 months ago
Adaptive View-Based Appearance Models
We present a method for online rigid object tracking using an adaptive view-based appearance model. When the object's pose trajectory crosses itself, our tracker has bounded ...
Louis-Philippe Morency, Ali Rahimi, Trevor Darrell
CVPR
2007
IEEE
16 years 9 months ago
OPTIMOL: automatic Online Picture collecTion via Incremental MOdel Learning
A well-built dataset is a necessary starting point for advanced computer vision research. It plays a crucial role in evaluation and provides a continuous challenge to stateof-the-...
Li-Jia Li, Gang Wang, Fei-Fei Li 0002
ICML
2007
IEEE
16 years 7 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
2000
IEEE
16 years 7 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...