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» A distributed machine learning framework
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CCS
2009
ACM
14 years 6 months ago
A framework for quantitative security analysis of machine learning
We propose a framework for quantitative security analysis of machine learning methods. Key issus of this framework are a formal specification of the deployed learning model and a...
Pavel Laskov, Marius Kloft
COLT
1998
Springer
14 years 3 months ago
Self Bounding Learning Algorithms
Most of the work which attempts to give bounds on the generalization error of the hypothesis generated by a learning algorithm is based on methods from the theory of uniform conve...
Yoav Freund
NIPS
2008
14 years 18 days ago
Asynchronous Distributed Learning of Topic Models
Distributed learning is a problem of fundamental interest in machine learning and cognitive science. In this paper, we present asynchronous distributed learning algorithms for two...
Arthur Asuncion, Padhraic Smyth, Max Welling
ICALT
2006
IEEE
14 years 5 months ago
A Study of Design Requirements for Mobile Learning Environments
This paper proposes a conceptual framework for mobile learning applications that provides systematic support for mobile learning experience design. It is based on a combination of...
David Parsons, Hokyoung Ryu, Mark Cranshaw
ICML
2005
IEEE
14 years 12 months ago
Experimental comparison between bagging and Monte Carlo ensemble classification
Properties of ensemble classification can be studied using the framework of Monte Carlo stochastic algorithms. Within this framework it is also possible to define a new ensemble c...
Roberto Esposito, Lorenza Saitta