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» Dimensionality reduction and generalization
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ICIP
2007
IEEE
15 years 7 months ago
Unsupervised Nonlinear Manifold Learning
This communication deals with data reduction and regression. A set of high dimensional data (e.g., images) usually has only a few degrees of freedom with corresponding variables t...
Matthieu Brucher, Christian Heinrich, Fabrice Heit...
CRYPTO
2011
Springer
191views Cryptology» more  CRYPTO 2011»
14 years 3 months ago
Analyzing Blockwise Lattice Algorithms Using Dynamical Systems
Strong lattice reduction is the key element for most attacks against lattice-based cryptosystems. Between the strongest but impractical HKZ reduction and the weak but fast LLL redu...
Guillaume Hanrot, Xavier Pujol, Damien Stehl&eacut...
IACR
2011
155views more  IACR 2011»
14 years 3 months ago
Terminating BKZ
Strong lattice reduction is the key element for most attacks against lattice-based cryptosystems. Between the strongest but impractical HKZ reduction and the weak but fast LLL redu...
Guillaume Hanrot, Xavier Pujol, Damien Stehl&eacut...
107
Voted
ICIP
1997
IEEE
16 years 5 months ago
A Differential Code for Shape Representation in Image Database Applications
A new method termed the vertex representation is presented for approximating the shapes of objects of arbitrary dimensionality d (e.g., 20, 30, etc.) with orthogonal (d - 1)-dimen...
Claudio Esperança, Hanan Samet
129
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NAACL
2001
15 years 5 months ago
Chunking with Support Vector Machines
We apply Support Vector Machines (SVMs) to identify English base phrases (chunks). SVMs are known to achieve high generalization performance even with input data of high dimension...
Taku Kudo, Yuji Matsumoto