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» Generation of Attributes for Learning Algorithms
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ICASSP
2011
IEEE
12 years 11 months ago
MCMC inference of the shape and variability of time-response signals
Signals in response to time-localized events of a common phenomenon tend to exhibit a common shape, but with variable time scale, amplitude, and delay across trials in many domain...
Dmitriy A. Katz-Rogozhnikov, Kush R. Varshney, Ale...
ICASSP
2011
IEEE
12 years 11 months ago
Approximation of pattern transformation manifolds with parametric dictionaries
The construction of low-dimensional models explaining highdimensional signal observations provides concise and efficient data representations. In this paper, we focus on pattern ...
Elif Vural, Pascal Frossard
JMLR
2012
11 years 10 months ago
SpeedBoost: Anytime Prediction with Uniform Near-Optimality
We present SpeedBoost, a natural extension of functional gradient descent, for learning anytime predictors, which automatically trade computation time for predictive accuracy by s...
Alexander Grubb, Drew Bagnell
ICCV
1998
IEEE
14 years 9 months ago
Multidimensional Morphable Models
We describe a exible model for representing images of objects of a certain class, known a priori, such as faces, and introduce a new algorithm for matching it to a novel image and...
Michael J. Jones, Tomaso Poggio
BPM
2009
Springer
116views Business» more  BPM 2009»
14 years 2 months ago
Discovering Reference Models by Mining Process Variants Using a Heuristic Approach
Abstract. Recently, a new generation of adaptive Process-Aware Information Systems (PAISs) has emerged, which enables structural process changes during runtime. Such flexibility, ...
Chen Li, Manfred Reichert, Andreas Wombacher