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ICML
2010
IEEE
14 years 10 months ago
Gaussian Processes Multiple Instance Learning
This paper proposes a multiple instance learning (MIL) algorithm for Gaussian processes (GP). The GP-MIL model inherits two crucial benefits from GP: (i) a principle manner of lea...
Minyoung Kim, Fernando De la Torre
ICIP
2007
IEEE
15 years 11 months ago
Faithful Shape Representation for 2D Gaussian Mixtures
It has been recently discovered that a faithful representation for the shape of some simple distributions can be constructed using invariant statistics [1, 2]. In this paper, we c...
Mireille Boutin, Mary I. Comer
ICML
2008
IEEE
15 years 10 months ago
Topologically-constrained latent variable models
In dimensionality reduction approaches, the data are typically embedded in a Euclidean latent space. However for some data sets this is inappropriate. For example, in human motion...
Raquel Urtasun, David J. Fleet, Andreas Geiger, Jo...
ECML
2005
Springer
15 years 3 months ago
U-Likelihood and U-Updating Algorithms: Statistical Inference in Latent Variable Models
Abstract. In this paper we consider latent variable models and introduce a new U-likelihood concept for estimating the distribution over hidden variables. One can derive an estimat...
JaeMo Sung, Sung Yang Bang, Seungjin Choi, Zoubin ...
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ICIP
2006
IEEE
15 years 11 months ago
Image Denoising with an Orientation-Adaptive Gaussian Scale Mixture Model
David K. Hammond, Eero P. Simoncelli