8970 search results - page 1510 / 1794 » Learning to Learn Causal Models |
164
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CORR
2010
Springer
15 years 5 months ago
2010
Springer
Structured output prediction is an important machine learning problem both in theory and practice, and the max-margin Markov network (M3 N) is an effective approach. All state-of-...
165
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ACL
2010
15 years 4 months ago
2010
Learning a tree substitution grammar is very challenging due to derivational ambiguity. Our recent approach used a Bayesian non-parametric model to induce good derivations from tr...
223
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AMDO
2010
Springer
15 years 4 months ago
2010
Springer
We propose a method for human full-body pose tracking from measurements of wearable inertial sensors. Since the data provided by such sensors is sparse, noisy and often ambiguous, ...
215
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BMVC
2010
15 years 4 months ago
2010
Gaussian processes have been widely used as a method for inferring the pose of articulated bodies directly from image data. While able to model complex non-linear functions, they ...
213
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ECAI
2010
Springer
15 years 4 months ago
2010
Springer
Conditional random fields (CRF) are widely used for predicting output variables that have some internal structure. Most of the CRF research has been done on structured classificati...