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» Predicting labels for dyadic data
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ACL
2009
13 years 7 months ago
A Non-negative Matrix Tri-factorization Approach to Sentiment Classification with Lexical Prior Knowledge
Sentiment classification refers to the task of automatically identifying whether a given piece of text expresses positive or negative opinion towards a subject at hand. The prolif...
Tao Li, Yi Zhang 0005, Vikas Sindhwani
ICCV
2011
IEEE
12 years 9 months ago
Relative Attributes
Human-nameable visual “attributes” can benefit various recognition tasks. However, existing techniques restrict these properties to categorical labels (for example, a person ...
Devi Parikh, Kristen Grauman
NPL
2006
172views more  NPL 2006»
13 years 9 months ago
Adapting RBF Neural Networks to Multi-Instance Learning
In multi-instance learning, the training examples are bags composed of instances without labels, and the task is to predict the labels of unseen bags through analyzing the training...
Min-Ling Zhang, Zhi-Hua Zhou
BMCBI
2010
153views more  BMCBI 2010»
13 years 10 months ago
Metamotifs - a generative model for building families of nucleotide position weight matrices
Background: Development of high-throughput methods for measuring DNA interactions of transcription factors together with computational advances in short motif inference algorithms...
Matias Piipari, Thomas A. Down, Tim J. P. Hubbard
ADMA
2006
Springer
143views Data Mining» more  ADMA 2006»
14 years 1 months ago
Robust Collective Classification with Contextual Dependency Network Models
Abstract. In order to exploit the dependencies in relational data to improve predictions, relational classification models often need to make simultaneous statistical judgments abo...
YongHong Tian, Tiejun Huang, Wen Gao