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» On Linear Cryptanalysis with Many Linear Approximations
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JMLR
2010
101views more  JMLR 2010»
14 years 8 months ago
Exploiting Feature Covariance in High-Dimensional Online Learning
Some online algorithms for linear classification model the uncertainty in their weights over the course of learning. Modeling the full covariance structure of the weights can prov...
Justin Ma, Alex Kulesza, Mark Dredze, Koby Crammer...
IPPS
2009
IEEE
15 years 8 months ago
Multi-users scheduling in parallel systems
We are interested in this paper to study scheduling problems in systems where many users compete to perform their respective jobs on shared parallel resources. Each user has speci...
Erik Saule, Denis Trystram
TSP
2008
151views more  TSP 2008»
15 years 1 months ago
Convergence Analysis of Reweighted Sum-Product Algorithms
Markov random fields are designed to represent structured dependencies among large collections of random variables, and are well-suited to capture the structure of real-world sign...
Tanya Roosta, Martin J. Wainwright, Shankar S. Sas...
ICML
2000
IEEE
16 years 2 months ago
Rates of Convergence for Variable Resolution Schemes in Optimal Control
This paper presents a general method to derive tight rates of convergence for numerical approximations in optimal control when we consider variable resolution grids. We study the ...
Andrew W. Moore, Rémi Munos
GFKL
2007
Springer
163views Data Mining» more  GFKL 2007»
15 years 5 months ago
Fast Support Vector Machine Classification of Very Large Datasets
In many classification applications, Support Vector Machines (SVMs) have proven to be highly performing and easy to handle classifiers with very good generalization abilities. Howe...
Janis Fehr, Karina Zapien Arreola, Hans Burkhardt