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AAAI
2006
15 years 6 months ago
Learning Partially Observable Action Models: Efficient Algorithms
We present tractable, exact algorithms for learning actions' effects and preconditions in partially observable domains. Our algorithms maintain a propositional logical repres...
Dafna Shahaf, Allen Chang, Eyal Amir
AAAI
1996
15 years 6 months ago
Learning to Take Actions
We formalize a model for supervised learning of action strategies in dynamic stochastic domains and show that PAC-learning results on Occam algorithms hold in this model as well. W...
Roni Khardon
144
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SIGCSE
2002
ACM
128views Education» more  SIGCSE 2002»
15 years 4 months ago
Enhancing the quality of learning and understanding of first-year mathematics for computer science related majors
Most courses on Discrete Mathematics are designed to emphasize problem solving, in general. When the goal is to cover the content, the learning and understanding takes a second pl...
Francis Suraweera
TNN
1998
112views more  TNN 1998»
15 years 4 months ago
A class of competitive learning models which avoids neuron underutilization problem
— In this paper, we study a qualitative property of a class of competitive learning (CL) models, which is called the multiplicatively biased competitive learning (MBCL) model, na...
Clifford Sze-Tsan Choy, Wan-Chi Siu
ICPR
2004
IEEE
16 years 6 months ago
Face Recognition Based on Discriminative Manifold Learning
In this paper, a discriminative manifold learning method for face recognition is proposed which achieved the discriminative embedding the high dimensional face data into a low dim...
Kap Luk Chan, Lei Wang, Yiming Wu