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NN
2002
Springer
113views Neural Networks» more  NN 2002»
15 years 6 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
VLSISP
2002
124views more  VLSISP 2002»
15 years 6 months ago
Agglomerative Learning Algorithms for General Fuzzy Min-Max Neural Network
In this paper two agglomerative learning algorithms based on new similarity measures defined for hyperbox fuzzy sets are proposed. They are presented in a context of clustering and...
Bogdan Gabrys
VL
2010
IEEE
160views Visual Languages» more  VL 2010»
15 years 5 months ago
Toward End-User Debugging of Machine-Learned Classifiers
Many machine-learning algorithms learn rules of behavior from individual end users, such as taskoriented desktop organizers and handwriting recognizers. These rules form a generat...
Todd Kulesza
INTERSPEECH
2010
15 years 1 months ago
Incremental word learning using large-margin discriminative training and variance floor estimation
We investigate incremental word learning in a Hidden Markov Model (HMM) framework suitable for human-robot interaction. In interactive learning, the tutoring time is a crucial fac...
Irene Ayllón Clemente, Martin Heckmann, Ale...
ICASSP
2011
IEEE
14 years 10 months ago
A sliding-window online fast variational sparse Bayesian learning algorithm
In this work a new online learning algorithm that uses automatic relevance determination (ARD) is proposed for fast adaptive nonlinear filtering. A sequential decision rule for i...
Thomas Buchgraber, Dmitriy Shutin, H. Vincent Poor