Št. zadetkov: 9
Video in druga učna gradiva
Oznake:
computer science;machine learning;markov processes
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unattainable fully annotated training data. While likelihood-based methods have been extensively explored, to our knowledge, le ...
Leto:
2008
Vir:
videolectures.net
Video in druga učna gradiva
Oznake:
computer science;machine learning;markov processes
Learning sparse Markov networks based on the maximum margin principle remains an open problem in structured prediction. In this paper, we proposed the Laplace max-margin Markov network (LapM3N), and a general class of Bayesian M3N (BM3N) of which the LapM3N is a special case and enjoys a sparse repr ...
Leto:
2008
Vir:
videolectures.net
Video in druga učna gradiva
Oznake:
computer science;machine learning;supervised learning;regression
Supervised topic models utilize document’s side information for discovering predictive low dimensional representations of documents;
and existing models apply likelihood-based estimation. In this paper, we present a max-margin supervised topic model for both continuous
and categorical response var ...
Leto:
2009
Vir:
videolectures.net
Video in druga učna gradiva
Oznake:
Sparsity is a desirable property in high dimensional learning. The $\ell_1$-norm regularization can lead to primal sparsity, while max-margin methods achieve dual sparsity; but achieving both in a single structured prediction model remains difficult. This paper presents an $\ell_1$-norm max-margin M ...
Leto:
2009
Vir:
videolectures.net
Video in druga učna gradiva
Oznake:
computer science;web mining;information extraction
Recent work has shown the effectiveness of leveraging layout and tag-tree structure for segmenting webpages and labeling HTML elements. However, how to effectively segment and label the text contents inside HTML elements is still an open problem. Since many text contents on a webpage are often text ...
Leto:
2007
Vir:
videolectures.net
Video in druga učna gradiva
Oznake:
computer science;machine learning;supervised learning
Max-margin Markov networks (M3N) have shown great promise in structured prediction and relational learning. Due to the KKT conditions, the M3N enjoys dual sparsity. However, the existing M3N formulation does not enjoy primal sparsity, which is a desirable property for selecting significant features ...
Leto:
2009
Vir:
videolectures.net
Video in druga učna gradiva
Oznake:
computer science;pattern recognition
Feature selection is an important task in order to achieve
better generalizability in high dimensional learning, and structure
learning of Markov random fields (MRFs) can automatically
discover the inherent structures underlying complex
data. Both problems can be cast as solving an ℓ1-norm
regulariz ...
Leto:
2010
Vir:
videolectures.net
Video in druga učna gradiva
Oznake:
computer science;machine learning
This year marks the 250th Anniversary of Bayes’ theorem, which is playing an increasingly important role in statistical applications. Existing Bayesian models, especially nonparametric Bayesian methods, rely heavily on specially conceived priors to incorporate domain knowledge for discovering improv ...
Leto:
2013
Vir:
videolectures.net
Taeg Sang Cho ,
Konstantinos Derpanis ,
Elena Bernardis ,
Tetsuro Morimoto ,
Miguel Granados ,
Jiejie Zhu ,
Marshall Tappen ,
Ce Liu ,
Lavanya Sharan ,
Yuanjie Zheng ,
Wei Xu ,
Jun Takamatsu ,
Daniel Freedman ,
Dror Aiger ,
Samuel Audet ,
Xinqi Chu ,
Chanki Yu ,
Bastian Goldluecke ,
Raj Gupta
Video in druga učna gradiva
Oznake:
computer science;computer vision;color, texture, illumination & reflectance
Leto:
2010
Vir:
videolectures.net