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ECCV
2010
Springer
14 years 9 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
SDM
2010
SIAM
200views Data Mining» more  SDM 2010»
14 years 11 months ago
Residual Bayesian Co-clustering for Matrix Approximation
In recent years, matrix approximation for missing value prediction has emerged as an important problem in a variety of domains such as recommendation systems, e-commerce and onlin...
Hanhuai Shan, Arindam Banerjee
FPGA
2006
ACM
224views FPGA» more  FPGA 2006»
15 years 1 months ago
Flexible implementation of genetic algorithms on FPGAs
In this paper, we propose a technique to flexibly implement genetic algorithms for various problems on FPGAs. For the purpose, we propose a basic architecture for GA which consist...
Tatsuhiro Tachibana, Yoshihiro Murata, Naoki Shiba...
CISS
2008
IEEE
15 years 4 months ago
On sparse representations of linear operators and the approximation of matrix products
—Thus far, sparse representations have been exploited largely in the context of robustly estimating functions in a noisy environment from a few measurements. In this context, the...
Mohamed-Ali Belabbas, Patrick J. Wolfe
PPOPP
1997
ACM
15 years 1 months ago
LoPC: Modeling Contention in Parallel Algorithms
Parallel algorithm designers need computational models that take first order system costs into account, but are also simple enough to use in practice. This paper introduces the L...
Matthew Frank, Anant Agarwal, Mary K. Vernon