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151
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CVIU
2011
14 years 7 months ago
Graph attribute embedding via Riemannian submersion learning
In this paper, we tackle the problem of embedding a set of relational structures into a metric space for purposes of matching and categorisation. To this end, we view the problem ...
Haifeng Zhao, Antonio Robles-Kelly, Jun Zhou, Jian...
136
Voted
NN
2002
Springer
113views Neural Networks» more  NN 2002»
15 years 3 months ago
Control of exploitation-exploration meta-parameter in reinforcement learning
In reinforcement learning (RL), the duality between exploitation and exploration has long been an important issue. This paper presents a new method that controls the balance betwe...
Shin Ishii, Wako Yoshida, Junichiro Yoshimoto
132
Voted
TMI
2008
138views more  TMI 2008»
15 years 3 months ago
Dynamic Positron Emission Tomography Data-Driven Analysis Using Sparse Bayesian Learning
A method is presented for the analysis of dynamic positron emission tomography (PET) data using sparse Bayesian learning. Parameters are estimated in a compartmental framework usin...
Jyh-Ying Peng, John A. D. Aston, R. N. Gunn, Cheng...
100
Voted
ICASSP
2010
IEEE
15 years 1 months ago
Efficient online learning with individual learning-rates for phoneme sequence recognition
We describe a fast and efficient online algorithm for phoneme sequence speech recognition. Our method is using a discriminative training to update the model parameters one utteran...
Koby Crammer
119
Voted
ACL
2009
15 years 1 months ago
Reinforcement Learning for Mapping Instructions to Actions
In this paper, we present a reinforcement learning approach for mapping natural language instructions to sequences of executable actions. We assume access to a reward function tha...
S. R. K. Branavan, Harr Chen, Luke S. Zettlemoyer,...