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IEEEMM
2007
146views more  IEEEMM 2007»
15 years 4 months ago
Learning Microarray Gene Expression Data by Hybrid Discriminant Analysis
— Microarray technology offers a high throughput means to study expression networks and gene regulatory networks in cells. The intrinsic nature of high dimensionality and small s...
Yijuan Lu, Qi Tian, Maribel Sanchez, Jennifer L. N...
JMLR
2010
143views more  JMLR 2010»
15 years 3 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
178views Data Mining» more  PKDD 2010»
15 years 3 months ago
Large-Scale Support Vector Learning with Structural Kernels
Abstract. In this paper, we present an extensive study of the cuttingplane algorithm (CPA) applied to structural kernels for advanced text classification on large datasets. In par...
Aliaksei Severyn, Alessandro Moschitti
CVPR
2011
IEEE
15 years 10 days ago
Learning Temporally Consistent Rigidities
We present a novel probabilistic framework for rigid tracking and segmentation of shapes observed from multiple cameras. Most existing methods have focused on solving each of thes...
Jean-Sebastien Franco, Edmond Boyer
JMLR
2010
147views more  JMLR 2010»
14 years 11 months ago
Spectral Regularization Algorithms for Learning Large Incomplete Matrices
We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we...
Rahul Mazumder, Trevor Hastie, Robert Tibshirani