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COLT
2007
Springer
14 years 4 months ago
Observational Learning in Random Networks
In the standard model of observational learning, n agents sequentially decide between two alternatives a or b, one of which is objectively superior. Their choice is based on a stoc...
Julian Lorenz, Martin Marciniszyn, Angelika Steger
CDC
2010
IEEE
196views Control Systems» more  CDC 2010»
13 years 4 months ago
Convergence and convergence rate of stochastic gradient search in the case of multiple and non-isolated extrema
The asymptotic behavior of stochastic gradient algorithms is studied. Relying on some results of differential geometry (Lojasiewicz gradient inequality), the almost sure pointconve...
Vladislav B. Tadic
EMNLP
2010
13 years 7 months ago
Enhancing Domain Portability of Chinese Segmentation Model Using Chi-Square Statistics and Bootstrapping
Almost all Chinese language processing tasks involve word segmentation of the language input as their first steps, thus robust and reliable segmentation techniques are always requ...
Baobao Chang, Dongxu Han
ALT
2004
Springer
14 years 6 months ago
Learning Languages from Positive Data and Negative Counterexamples
In this paper we introduce a paradigm for learning in the limit of potentially infinite languages from all positive data and negative counterexamples provided in response to the ...
Sanjay Jain, Efim B. Kinber
ML
2008
ACM
115views Machine Learning» more  ML 2008»
13 years 9 months ago
Calling variadic functions from a strongly-typed language
The importance of providing a mechanism to call C functions from high-level languages has been understood for many years and, these days, almost all statically-typed high-level-la...
Matthias Blume, Mike Rainey, John H. Reppy