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» A Framework for Multiple-Instance Learning
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JMLR
2002
135views more  JMLR 2002»
15 years 5 months ago
Covering Number Bounds of Certain Regularized Linear Function Classes
Recently, sample complexity bounds have been derived for problems involving linear functions such as neural networks and support vector machines. In many of these theoretical stud...
Tong Zhang
CORR
2010
Springer
183views Education» more  CORR 2010»
15 years 4 months ago
Discovering shared and individual latent structure in multiple time series
This paper proposes a nonparametric Bayesian method for exploratory data analysis and feature construction in continuous time series. Our method focuses on understanding shared fe...
Suchi Saria, Daphne Koller, Anna Penn
179
Voted
PR
2010
163views more  PR 2010»
15 years 4 months ago
Optimal feature selection for support vector machines
Selecting relevant features for Support Vector Machine (SVM) classifiers is important for a variety of reasons such as generalization performance, computational efficiency, and ...
Minh Hoai Nguyen, Fernando De la Torre
EMNLP
2010
15 years 4 months ago
Turbo Parsers: Dependency Parsing by Approximate Variational Inference
We present a unified view of two state-of-theart non-projective dependency parsers, both approximate: the loopy belief propagation parser of Smith and Eisner (2008) and the relaxe...
André F. T. Martins, Noah A. Smith, Eric P....
EMNLP
2010
15 years 4 months ago
Incorporating Content Structure into Text Analysis Applications
In this paper, we investigate how modeling content structure can benefit text analysis applications such as extractive summarization and sentiment analysis. This follows the lingu...
Christina Sauper, Aria Haghighi, Regina Barzilay