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» Parameterized Learning Complexity
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119
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PAMI
2006
185views more  PAMI 2006»
15 years 3 months ago
Generic Object Recognition with Boosting
This paper explores the power and the limitations of weakly supervised categorization. We present a complete framework that starts with the extraction of various local regions of e...
Andreas Opelt, Axel Pinz, Michael Fussenegger, Pet...
137
Voted
JIRS
2007
116views more  JIRS 2007»
15 years 3 months ago
Recognition of Human Motion From Qualitative Normalised Templates
Abstract This paper proposes a Qualitative Normalised Templates (QNTs) framework for solving the human motion classification problem. In contrast to other human motion classifica...
Chee Seng Chan, Honghai Liu, David J. Brown
ALIFE
1998
15 years 3 months ago
Evolutionary Body Building: Adaptive Physical Designs for Robots
Creating artificial life forms through evolutionary robotics faces a “chicken and egg” problem: learning to control a complex body is dominated by problems specific to its s...
Pablo Funes, Jordan B. Pollack
164
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SIAMCOMP
1998
92views more  SIAMCOMP 1998»
15 years 3 months ago
Surface Approximation and Geometric Partitions
Motivated by applications in computer graphics, visualization, and scienti c computation, we study the computational complexity of the following problem: Given a set S of n points...
Pankaj K. Agarwal, Subhash Suri
JAIR
2010
145views more  JAIR 2010»
15 years 2 months ago
Planning with Noisy Probabilistic Relational Rules
Noisy probabilistic relational rules are a promising world model representation for several reasons. They are compact and generalize over world instantiations. They are usually in...
Tobias Lang, Marc Toussaint