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» Density Estimation: Nonparametric Techniques
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DATE
2009
IEEE
105views Hardware» more  DATE 2009»
15 years 4 months ago
Enrichment of limited training sets in machine-learning-based analog/RF test
Abstract— This paper discusses the generation of informationrich, arbitrarily-large synthetic data sets which can be used to (a) efficiently learn tests that correlate a set of ...
Haralampos-G. D. Stratigopoulos, Salvador Mir, Yio...
ECCV
2010
Springer
15 years 2 months ago
Weakly Supervised Shape Based Object Detection with Particle Filter
Abstract. We describe an efficient approach to construct shape models composed of contour parts with partially-supervised learning. The proposed approach can easily transfer parts ...
CSDA
2007
102views more  CSDA 2007»
14 years 9 months ago
Smooth functions and local extreme values
Given a sample of n observations y1, . . . , yn at time points t1, . . . , tn we consider the problem of specifying a function ˜f such that ˜f • is smooth, • fits the data ...
A. Kovac
JAIR
1998
198views more  JAIR 1998»
14 years 9 months ago
Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Alberto Ruiz, Pedro E. López-de-Teruel, M. ...
AMDO
2010
Springer
14 years 7 months ago
Compatible Particles for Part-Based Tracking
Particle Filter methods are one of the dominant tracking paradigms due to its ability to handle non-gaussian processes, multimodality and temporal consistency. Traditionally, the e...
Brais Martínez, Marc Vivet, Xavier Binefa