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CORR
2010
Springer
105views Education» more  CORR 2010»
13 years 2 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»
13 years 11 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
11 years 9 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
14 years 9 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
ALT
2006
Springer
14 years 4 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