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JMLR
2008
230views more  JMLR 2008»
13 years 8 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
P2P
2006
IEEE
153views Communications» more  P2P 2006»
14 years 1 months ago
Internet-Scale Storage Systems under Churn -- A Study of the Steady-State using Markov Models
Content storage in a distributed collaborative environment uses redundancy for better resilience and thus provides good availability and durability. In a peer-to-peer environment,...
Anwitaman Datta, Karl Aberer
JCC
2007
127views more  JCC 2007»
13 years 7 months ago
Prediction of GFP spectral properties using artificial neural network
Abstract: In this study, we applied artificial neural network, implementing the backpropagation algorithm, for the prediction of the excitation and emission maxima of green fluores...
Chanin Nantasenamat, Chartchalerm Isarankura-Na-Ay...
IPM
2008
100views more  IPM 2008»
13 years 8 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...
CRYPTO
2010
Springer
228views Cryptology» more  CRYPTO 2010»
13 years 9 months ago
On Generalized Feistel Networks
We prove beyond-birthday-bound security for most of the well-known types of generalized Feistel networks: (1) unbalanced Feistel networks, where the n-bit to m-bit round functions ...
Viet Tung Hoang, Phillip Rogaway