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» On the monotonization of the training set
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IJON
2000
81views more  IJON 2000»
15 years 12 days ago
Initialization by selection for wavelet network training
We present an original initialization procedure for the parameters of feedforward wavelet networks, prior to training by gradient-based techniques. It takes advantage of wavelet f...
Yacine Oussar, Gérard Dreyfus
98
Voted
CVPR
2007
IEEE
16 years 2 months ago
Face Recognition using Discriminatively Trained Orthogonal Rank One Tensor Projections
We propose a method for face recognition based on a discriminative linear projection. In this formulation images are treated as tensors, rather than the more conventional vector o...
Gang Hua, Paul A. Viola, Steven M. Drucker
81
Voted
ICPR
2004
IEEE
16 years 1 months ago
Decoder Banks: Versatility, Automation, and High Accuracy without Supervised Training
A methodology using decoder banks is proposed for high-accuracy, fully automatic recognition of machine printed text across a wide range of challenging image qualities, without re...
Henry S. Baird, Prateek Sarkar
108
Voted
EMNLP
2010
14 years 10 months ago
Joint Training and Decoding Using Virtual Nodes for Cascaded Segmentation and Tagging Tasks
Many sequence labeling tasks in NLP require solving a cascade of segmentation and tagging subtasks, such as Chinese POS tagging, named entity recognition, and so on. Traditional p...
Xian Qian, Qi Zhang, Yaqian Zhou, Xuanjing Huang, ...
ICML
2006
IEEE
16 years 1 months ago
Accelerated training of conditional random fields with stochastic gradient methods
We apply Stochastic Meta-Descent (SMD), a stochastic gradient optimization method with gain vector adaptation, to the training of Conditional Random Fields (CRFs). On several larg...
S. V. N. Vishwanathan, Nicol N. Schraudolph, Mark ...