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SAC
2005
ACM
16 years 9 days ago
Stochastic scheduling of active support vector learning algorithms
Active learning is a generic approach to accelerate training of classifiers in order to achieve a higher accuracy with a small number of training examples. In the past, simple ac...
Gaurav Pandey, Himanshu Gupta, Pabitra Mitra
ASIACRYPT
2003
Springer
15 years 12 months ago
Generalized Powering Functions and Their Application to Digital Signatures
This paper investigates some modular powering functions suitable for cryptography. It is well known that the Rabin encryption function is a 4-to-1 mapping and breaking its one-wayn...
Hisayoshi Sato, Tsuyoshi Takagi, Satoru Tezuka, Ka...
COCOON
2005
Springer
15 years 8 months ago
Solovay Reducibility on D-c.e Real Numbers
A c.e. real x is Solovay reducible to another c.e. real y if x can be approximated at least as efficiently as y by means of increasing computable sequences of rational numbers. The...
Robert Rettinger, Xizhong Zheng
213
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CISS
2011
IEEE
14 years 10 months ago
The Restricted Isometry Property for block diagonal matrices
—In compressive sensing (CS), the Restricted Isometry Property (RIP) is a powerful condition on measurement operators which ensures robust recovery of sparse vectors is possible ...
Han Lun Yap, Armin Eftekhari, Michael B. Wakin, Ch...
ICASSP
2009
IEEE
16 years 1 months ago
Structured variational methods for distributed inference in wireless ad hoc and sensor networks
Abstract –In this paper, a variational message passing framework is proposed for Markov random fields, which is computationally more efficient and admits wider applicability comp...
Yanbing Zhang, Huaiyu Dai