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» Structured metric learning for high dimensional problems
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NIPS
2007
13 years 9 months ago
Multi-Task Learning via Conic Programming
When we have several related tasks, solving them simultaneously is shown to be more effective than solving them individually. This approach is called multi-task learning (MTL) and...
Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama, ...
ICCAD
2006
IEEE
152views Hardware» more  ICCAD 2006»
14 years 4 months ago
Performance-oriented statistical parameter reduction of parameterized systems via reduced rank regression
Process variations in modern VLSI technologies are growing in both magnitude and dimensionality. To assess performance variability, complex simulation and performance models param...
Zhuo Feng, Peng Li
ICML
2007
IEEE
14 years 8 months ago
Regression on manifolds using kernel dimension reduction
We study the problem of discovering a manifold that best preserves information relevant to a nonlinear regression. Solving this problem involves extending and uniting two threads ...
Jens Nilsson, Fei Sha, Michael I. Jordan
CVPR
2010
IEEE
14 years 3 months ago
SPEC Hashing: Similarity Preserving algorithm for Entropy-based Coding
Searching approximate nearest neighbors in large scale high dimensional data set has been a challenging problem. This paper presents a novel and fast algorithm for learning binary...
Ruei-Sung Lin, David Ross, Jay Yagnik
SIGIR
2003
ACM
14 years 28 days ago
A maximal figure-of-merit learning approach to text categorization
A novel maximal figure-of-merit (MFoM) learning approach to text categorization is proposed. Different from the conventional techniques, the proposed MFoM method attempts to integ...
Sheng Gao, Wen Wu, Chin-Hui Lee, Tat-Seng Chua