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» Reinforcement learning with Gaussian processes
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108
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ICML
2006
IEEE
16 years 2 months ago
Collaborative ordinal regression
Ordinal regression has become an effective way of learning user preferences, but most of research only focuses on single regression problem. In this paper we introduce collaborati...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
126
Voted
ICML
2008
IEEE
16 years 2 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...
ICIP
2007
IEEE
16 years 3 months ago
Color Image Superresolution Based on a Stochastic Combinational Classification-Regression Algorithm
Abstract - The proposed algorithm in this work provides superresolution for color images by using a learning based technique that utilizes both generative and discriminant approach...
Karl S. Ni, Truong Q. Nguyen
ICML
2005
IEEE
16 years 2 months ago
Healing the relevance vector machine through augmentation
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
Carl Edward Rasmussen, Joaquin Quiñonero Ca...
ISM
2008
IEEE
110views Multimedia» more  ISM 2008»
15 years 8 months ago
A Hardware-Independent Fast Logarithm Approximation with Adjustable Accuracy
Many multimedia applications rely on the computation of logarithms, for example, when estimating log-likelihoods for Gaussian Mixture Models. Knowing of the demand to compute loga...
Oriol Vinyals, Gerald Friedland