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AR
2007
105views more  AR 2007»
13 years 10 months ago
Reinforcement learning of a continuous motor sequence with hidden states
—Reinforcement learning is the scheme for unsupervised learning in which robots are expected to acquire behavior skills through self-explorations based on reward signals. There a...
Hiroaki Arie, Tetsuya Ogata, Jun Tani, Shigeki Sug...
ML
2006
ACM
121views Machine Learning» more  ML 2006»
13 years 10 months ago
Model-based transductive learning of the kernel matrix
This paper addresses the problem of transductive learning of the kernel matrix from a probabilistic perspective. We define the kernel matrix as a Wishart process prior and construc...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
AIEDU
2004
105views more  AIEDU 2004»
13 years 10 months ago
Evaluating the REDEEM Authoring Tool: Can Teachers Create Effective Learning Environments?
The REDEEM authoring environment allows teachers to create learning environments from existing computer-based training (CBT) by imposing their pedagogical preferences about how stu...
Shaaron Ainsworth, Shirley Grimshaw
TNN
1998
111views more  TNN 1998»
13 years 9 months ago
Asymptotic distributions associated to Oja's learning equation for neural networks
— In this paper, we perform a complete asymptotic performance analysis of the stochastic approximation algorithm (denoted subspace network learning algorithm) derived from Oja’...
Jean Pierre Delmas, Jean-Francois Cardos
ICML
2008
IEEE
14 years 10 months ago
Boosting with incomplete information
In real-world machine learning problems, it is very common that part of the input feature vector is incomplete: either not available, missing, or corrupted. In this paper, we pres...
Feng Jiao, Gholamreza Haffari, Greg Mori, Shaojun ...