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» New Regularized Algorithms for Transductive Learning
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100
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CVPR
2007
IEEE
16 years 1 months ago
Concurrent Multiple Instance Learning for Image Categorization
We propose a new multiple instance learning (MIL) algorithm to learn image categories. Unlike existing MIL algorithms, in which the individual instances in a bag are assumed to be...
Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Tao Mei, Jin...
100
Voted
NIPS
2001
15 years 1 months ago
Online Learning with Kernels
Abstract--Kernel-based algorithms such as support vector machines have achieved considerable success in various problems in batch setting, where all of the training data is availab...
Jyrki Kivinen, Alex J. Smola, Robert C. Williamson
ICML
2009
IEEE
16 years 13 days ago
Robust bounds for classification via selective sampling
We introduce a new algorithm for binary classification in the selective sampling protocol. Our algorithm uses Regularized Least Squares (RLS) as base classifier, and for this reas...
Nicolò Cesa-Bianchi, Claudio Gentile, Franc...
PLDI
2011
ACM
14 years 2 months ago
The tao of parallelism in algorithms
For more than thirty years, the parallel programming community has used the dependence graph as the main abstraction for reasoning about and exploiting parallelism in “regularâ€...
Keshav Pingali, Donald Nguyen, Milind Kulkarni, Ma...
93
Voted
JMLR
2010
106views more  JMLR 2010»
14 years 6 months ago
Why Does Unsupervised Pre-training Help Deep Learning?
Much recent research has been devoted to learning algorithms for deep architectures such as Deep Belief Networks and stacks of auto-encoder variants, with impressive results obtai...
Dumitru Erhan, Yoshua Bengio, Aaron C. Courville, ...