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JMLR
2010
161views more  JMLR 2010»
13 years 3 months ago
Dual Averaging Methods for Regularized Stochastic Learning and Online Optimization
We consider regularized stochastic learning and online optimization problems, where the objective function is the sum of two convex terms: one is the loss function of the learning...
Lin Xiao
VLSM
2005
Springer
14 years 2 months ago
A Surface Reconstruction Method for Highly Noisy Point Clouds
In this paper we propose a surface reconstruction method for highly noisy and non-uniform data based on minimal surface model and tensor voting method. To deal with ill-posedness, ...
DanFeng Lu, HongKai Zhao, Ming Jiang 0001, ShuLin ...
PKDD
2009
Springer
153views Data Mining» more  PKDD 2009»
14 years 3 months ago
Subspace Regularization: A New Semi-supervised Learning Method
Most existing semi-supervised learning methods are based on the smoothness assumption that data points in the same high density region should have the same label. This assumption, ...
Yan-Ming Zhang, Xinwen Hou, Shiming Xiang, Cheng-L...
MIAR
2008
IEEE
14 years 3 months ago
A Surface-Based Fractal Information Dimension Method for Cortical Complexity Analysis
In this paper, we proposed a new surface-based fractal information dimension (FID) method to quantify the cortical complexity. Unlike the traditional box-counting method to measure...
Yuanchao Zhang, Jiefeng Jiang, Lei Lin, Feng Shi, ...
KDD
2008
ACM
167views Data Mining» more  KDD 2008»
14 years 9 months ago
A sequential dual method for large scale multi-class linear svms
Efficient training of direct multi-class formulations of linear Support Vector Machines is very useful in applications such as text classification with a huge number examples as w...
S. Sathiya Keerthi, S. Sundararajan, Kai-Wei Chang...