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» Stochastic complexity in learning
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DATE
2008
IEEE
136views Hardware» more  DATE 2008»
14 years 2 months ago
A Framework of Stochastic Power Management Using Hidden Markov Model
- The effectiveness of stochastic power management relies on the accurate system and workload model and effective policy optimization. Workload modeling is a machine learning proce...
Ying Tan, Qinru Qiu
COLING
2010
13 years 2 months ago
Broad Coverage Multilingual Deep Sentence Generation with a Stochastic Multi-Level Realizer
Most of the known stochastic sentence generators use syntactically annotated corpora, performing the projection to the surface in one stage. However, in full-fledged text generati...
Bernd Bohnet, Leo Wanner, Simon Mille, Alicia Burg...
ICPR
2010
IEEE
13 years 10 months ago
Fast Training of Object Detection Using Stochastic Gradient Descent
Training datasets for object detection problems are typically very large and Support Vector Machine (SVM) implementations are computationally complex. As opposed to these complex ...
Rob Wijnhoven, Peter H. N. De With
ATAL
2006
Springer
13 years 11 months ago
Learning the required number of agents for complex tasks
Coordinating agents in a complex environment is a hard problem, but it can become even harder when certain characteristics of the tasks, like the required number of agents, are un...
Sébastien Paquet, Brahim Chaib-draa

Lecture Notes
592views
15 years 7 months ago
Stochastic Differential Equations
These lecture notes have been developed over several semesters with the assistance of students in the course. For many (most) results, only incomplete proofs are given. Gaps in the...
Thomas G. Kurtz