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NIPS
2007
15 years 9 months ago
A General Boosting Method and its Application to Learning Ranking Functions for Web Search
We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...
Zhaohui Zheng, Hongyuan Zha, Tong Zhang, Olivier C...
AAAI
2006
15 years 9 months ago
Semi-supervised Multi-label Learning by Constrained Non-negative Matrix Factorization
We present a novel framework for multi-label learning that explicitly addresses the challenge arising from the large number of classes and a small size of training data. The key a...
Yi Liu, Rong Jin, Liu Yang
NIPS
1997
15 years 9 months ago
Learning to Schedule Straight-Line Code
Program execution speed on modern computers is sensitive, by a factor of two or more, to the order in which instructions are presented to the processor. To realize potential execu...
J. Eliot B. Moss, Paul E. Utgoff, John Cavazos, Do...
CVPR
2010
IEEE
15 years 7 months ago
Learning kernels for variants of normalized cuts: Convex relaxations and applications
We propose a new algorithm for learning kernels for variants of the Normalized Cuts (NCuts) objective – i.e., given a set of training examples with known partitions, how should ...
Lopamudra Mukherjee, Vikas Singh, Jiming Peng, Chr...
TCBB
2008
120views more  TCBB 2008»
15 years 7 months ago
Learning Scoring Schemes for Sequence Alignment from Partial Examples
When aligning biological sequences, the choice of scoring scheme is critical. Even small changes in gap penalties, for example, can yield radically different alignments. A rigorous...
Eagu Kim, John D. Kececioglu