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» Kernelization for Convex Recoloring
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ICPP
1995
IEEE
13 years 11 months ago
Fusion of Loops for Parallelism and Locality
Loop fusion improves data locality and reduces synchronization in data-parallel applications. However, loop fusion is not always legal. Even when legal, fusion may introduce loop-...
Naraig Manjikian, Tarek S. Abdelrahman
SDM
2008
SIAM
150views Data Mining» more  SDM 2008»
13 years 8 months ago
A Stagewise Least Square Loss Function for Classification
This paper presents a stagewise least square (SLS) loss function for classification. It uses a least square form within each stage to approximate a bounded monotonic nonconvex los...
Shuang-Hong Yang, Bao-Gang Hu
NIPS
2004
13 years 8 months ago
Maximum Margin Clustering
We propose a new method for clustering based on finding maximum margin hyperplanes through data. By reformulating the problem in terms of the implied equivalence relation matrix, ...
Linli Xu, James Neufeld, Bryce Larson, Dale Schuur...
ICML
2010
IEEE
13 years 8 months ago
Learning Sparse SVM for Feature Selection on Very High Dimensional Datasets
A sparse representation of Support Vector Machines (SVMs) with respect to input features is desirable for many applications. In this paper, by introducing a 0-1 control variable t...
Mingkui Tan, Li Wang, Ivor W. Tsang
CORR
2010
Springer
95views Education» more  CORR 2010»
13 years 7 months ago
Optimization and Convergence of Observation Channels in Stochastic Control
This paper studies the optimization of observation channels (stochastic kernels) in partially observed stochastic control problems. In particular, existence, continuity, and convex...
Serdar Yüksel, Tamás Linder