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» A Minimax Method for Learning Functional Networks
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ICONIP
2008
13 years 9 months ago
On Node-Fault-Injection Training of an RBF Network
Abstract. While injecting fault during training has long been demonstrated as an effective method to improve fault tolerance of a neural network, not much theoretical work has been...
John Sum, Chi-Sing Leung, Kevin Ho
ICTAI
2009
IEEE
14 years 2 months ago
EBLearn: Open-Source Energy-Based Learning in C++
Energy-based learning (EBL) is a general framework to describe supervised and unsupervised training methods for probabilistic and non-probabilistic factor graphs. An energy-based ...
Pierre Sermanet, Koray Kavukcuoglu, Yann LeCun
IPM
2008
100views more  IPM 2008»
13 years 7 months ago
Query-level loss functions for information retrieval
Many machine learning technologies such as support vector machines, boosting, and neural networks have been applied to the ranking problem in information retrieval. However, since...
Tao Qin, Xu-Dong Zhang, Ming-Feng Tsai, De-Sheng W...
MS
2003
13 years 9 months ago
Information-theoretic Competitive Learning
— In this paper, we propose a new supervised learning method whereby information is controlled by the associated cost in an intermediate layer, and in an output layer, errors bet...
Ryotaro Kamimura
CVPR
2005
IEEE
14 years 9 months ago
Learning a Similarity Metric Discriminatively, with Application to Face Verification
We present a method for training a similarity metric from data. The method can be used for recognition or verification applications where the number of categories is very large an...
Sumit Chopra, Raia Hadsell, Yann LeCun