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CN
2010
110views more  CN 2010»
15 years 4 months ago
End-to-end quality of service seen by applications: A statistical learning approach
The focus of this work is on the estimation of quality of service (QoS) parameters seen by an application. Our proposal is based on end-to-end active measurements and statistical ...
Pablo Belzarena, Laura Aspirot
NEUROSCIENCE
2001
Springer
15 years 8 months ago
Finite-State Computation in Analog Neural Networks: Steps towards Biologically Plausible Models?
Abstract. Finite-state machines are the most pervasive models of computation, not only in theoretical computer science, but also in all of its applications to real-life problems, a...
Mikel L. Forcada, Rafael C. Carrasco
ACL
2010
15 years 2 months ago
cdec: A Decoder, Alignment, and Learning Framework for Finite-State and Context-Free Translation Models
We present cdec, an open source framework for decoding, aligning with, and training a number of statistical machine translation models, including word-based models, phrase-based m...
Chris Dyer, Adam Lopez, Juri Ganitkevitch, Jonatha...
ICML
2010
IEEE
15 years 2 months ago
Constructing States for Reinforcement Learning
POMDPs are the models of choice for reinforcement learning (RL) tasks where the environment cannot be observed directly. In many applications we need to learn the POMDP structure ...
M. M. Hassan Mahmud
TNN
2008
171views more  TNN 2008»
15 years 4 months ago
Adaptive Dynamic Inversion via Time-Scale Separation
Abstract--This paper presents a full state feedback adaptive dynamic inversion method for uncertain systems that depend nonlinearly upon the control input. Using a specialized set ...
Naira Hovakimyan, E. Lavretsky, Chengyu Cao