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EMNLP
2011
12 years 4 months ago
Structured Sparsity in Structured Prediction
Linear models have enjoyed great success in structured prediction in NLP. While a lot of progress has been made on efficient training with several loss functions, the problem of ...
André F. T. Martins, Noah A. Smith, M&aacut...
TIP
2011
123views more  TIP 2011»
12 years 11 months ago
Spatial Sparsity-Induced Prediction (SIP) for Images and Video: A Simple Way to Reject Structured Interference
We propose a prediction technique that is geared toward forming successful estimates of a signal based on a correlated anchor signal that is contaminated with complex interference...
Gang Hua, Onur G. Guleryuz
ACL
2011
12 years 8 months ago
Discovering Sociolinguistic Associations with Structured Sparsity
We present a method to discover robust and interpretable sociolinguistic associations from raw geotagged text data. Using aggregate demographic statistics about the authors’ geo...
Jacob Eisenstein, Noah A. Smith, Eric P. Xing
ICML
2009
IEEE
14 years 5 months ago
Boosting with structural sparsity
Despite popular belief, boosting algorithms and related coordinate descent methods are prone to overfitting. We derive modifications to AdaBoost and related gradient-based coordin...
John Duchi, Yoram Singer
ICML
2010
IEEE
13 years 5 months ago
Tree-Guided Group Lasso for Multi-Task Regression with Structured Sparsity
We consider the problem of learning a sparse multi-task regression, where the structure in the outputs can be represented as a tree with leaf nodes as outputs and internal nodes a...
Seyoung Kim, Eric P. Xing