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JMLR
2010
143views more  JMLR 2010»
15 years 5 months ago
A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning
We extend the well-known BFGS quasi-Newton method and its memory-limited variant LBFGS to the optimization of nonsmooth convex objectives. This is done in a rigorous fashion by ge...
Jin Yu, S. V. N. Vishwanathan, Simon Günter, ...
PKDD
2010
Springer
169views Data Mining» more  PKDD 2010»
15 years 4 months ago
Efficient and Numerically Stable Sparse Learning
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
Sihong Xie, Wei Fan, Olivier Verscheure, Jiangtao ...
CVPR
2011
IEEE
15 years 3 months ago
Nonparametric Density Estimation on A Graph: Learning Framework, Fast Approximation and Application in Image Segmentation
We present a novel framework for tree-structure embedded density estimation and its fast approximation for mode seeking. The proposed method could find diverse applications in co...
Zhiding Yu, Oscar Au, Ketan Tang
IJRR
2011
126views more  IJRR 2011»
15 years 1 months ago
Optimization and learning for rough terrain legged locomotion
We present a novel approach to legged locomotion over rough terrain that is thoroughly rooted in optimization. This approach relies on a hierarchy of fast, anytime algorithms to p...
Matthew Zucker, Nathan D. Ratliff, Martin Stolle, ...
CORR
2011
Springer
161views Education» more  CORR 2011»
14 years 10 months ago
Doubly Robust Policy Evaluation and Learning
We study decision making in environments where the reward is only partially observed, but can be modeled as a function of an action and an observed context. This setting, known as...
Miroslav Dudík, John Langford, Lihong Li