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EMNLP
2011
12 years 10 months ago
Dual Decomposition with Many Overlapping Components
Dual decomposition has been recently proposed as a way of combining complementary models, with a boost in predictive power. However, in cases where lightweight decompositions are ...
André L. Martins, Noah A. Smith, Már...
ICCV
2011
IEEE
12 years 11 months ago
Informative Feature Selection for Object Recognition via Sparse PCA
Bag-of-words (BoW) methods are a popular class of object recognition methods that use image features (e.g., SIFT) to form visual dictionaries and subsequent histogram vectors to r...
Nikhil Naikal, Allen Y. Yang, S. Shankar Sastry
JOTA
2011
78views more  JOTA 2011»
13 years 1 months ago
Outer Trust-Region Method for Constrained Optimization
Given an algorithm A for solving some mathematical problem based on the iterative solution of simpler subproblems, an Outer Trust-Region (OTR) modification of A is the result of ...
Ernesto G. Birgin, Emerson V. Castelani, Andr&eacu...
SIAMJO
2011
13 years 5 months ago
Recovering Low-Rank and Sparse Components of Matrices from Incomplete and Noisy Observations
Many applications arising in a variety of fields can be well illustrated by the task of recovering the low-rank and sparse components of a given matrix. Recently, it is discovered...
Min Tao, Xiaoming Yuan
TKDE
2008
118views more  TKDE 2008»
13 years 10 months ago
A Lagrangian Approach for Multiple Personalized Campaigns
The multicampaign assignment problem is a campaign model to overcome the multiple-recommendation problem that occurs when conducting several personalized campaigns simultaneously. ...
Yong-Hyuk Kim, Yourim Yoon, Byung Ro Moon