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ICML
2010
IEEE
13 years 8 months ago
A scalable trust-region algorithm with application to mixed-norm regression
We present a new algorithm for minimizing a convex loss-function subject to regularization. Our framework applies to numerous problems in machine learning and statistics; notably,...
Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon
ICML
2010
IEEE
13 years 8 months ago
A Fast Augmented Lagrangian Algorithm for Learning Low-Rank Matrices
We propose a general and efficient algorithm for learning low-rank matrices. The proposed algorithm converges super-linearly and can keep the matrix to be learned in a compact fac...
Ryota Tomioka, Taiji Suzuki, Masashi Sugiyama, His...
FGR
2008
IEEE
195views Biometrics» more  FGR 2008»
14 years 1 months ago
Regularized active shape model for shape alignment
Active shape model (ASM) statistically represents a shape by a set of well-defined landmark points and models object variations using principal component analysis (PCA). However, ...
Ran He, Zhen Lei, Xiaotong Yuan, Stan Z. Li
ICML
2009
IEEE
14 years 8 months ago
Regularization and feature selection in least-squares temporal difference learning
We consider the task of reinforcement learning with linear value function approximation. Temporal difference algorithms, and in particular the Least-Squares Temporal Difference (L...
J. Zico Kolter, Andrew Y. Ng
CIKM
2010
Springer
13 years 4 months ago
Regularization and feature selection for networked features
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
Hongliang Fei, Brian Quanz, Jun Huan