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96
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CORR
2010
Springer
105views Education» more  CORR 2010»
14 years 4 months ago
Universal and Robust Distributed Network Codes
Random linear network codes can be designed and implemented in a distributed manner, with low computational complexity. However, these codes are classically implemented [1] over fi...
Tracey Ho, Sidharth Jaggi, Svitlana Vyetrenko, Lin...
STOC
1991
ACM
84views Algorithms» more  STOC 1991»
15 years 1 months ago
Self-Testing/Correcting for Polynomials and for Approximate Functions
The study of self-testing/correcting programs was introduced in [8] in order to allow one to use program P to compute function f without trusting that P works correctly. A self-te...
Peter Gemmell, Richard J. Lipton, Ronitt Rubinfeld...
JMLR
2012
12 years 12 months ago
Metric and Kernel Learning Using a Linear Transformation
Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
Prateek Jain, Brian Kulis, Jason V. Davis, Inderji...
ICCV
2007
IEEE
15 years 11 months ago
Applications of parametric maxflow in computer vision
The maximum flow algorithm for minimizing energy functions of binary variables has become a standard tool in computer vision. In many cases, unary costs of the energy depend linea...
Vladimir Kolmogorov, Yuri Boykov, Carsten Rother
100
Voted
ALT
2006
Springer
15 years 6 months ago
Learning Linearly Separable Languages
This paper presents a novel paradigm for learning languages that consists of mapping strings to an appropriate high-dimensional feature space and learning a separating hyperplane i...
Leonid Kontorovich, Corinna Cortes, Mehryar Mohri