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» Generation of Attributes for Learning Algorithms
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ICASSP
2011
IEEE
14 years 3 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
14 years 3 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
13 years 2 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
16 years 1 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»
15 years 6 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