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ML
2012
ACM
413views Machine Learning» more  ML 2012»
13 years 10 months ago
Gradient-based boosting for statistical relational learning: The relational dependency network case
Dependency networks approximate a joint probability distribution over multiple random variables as a product of conditional distributions. Relational Dependency Networks (RDNs) are...
Sriraam Natarajan, Tushar Khot, Kristian Kersting,...
AAAI
2012
13 years 5 months ago
A Sequential Decision Approach to Ordinal Preferences in Recommender Systems
We propose a novel sequential decision approach to modeling ordinal ratings in collaborative filtering problems. The rating process is assumed to start from the lowest level, eva...
Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
IEEEARES
2009
IEEE
15 years 9 months ago
Deconvolving Protected Signals
Abstract—The variable clock (VC) side-channel countermeasure consists in clocking a chip with an internal oscillator whose parameters (frequency, duty cycle, shape etc.) vary ran...
Mohaned Kafi, Sylvain Guilley, S. Marcello, David ...
ICA
2007
Springer
15 years 9 months ago
Modeling and Estimation of Dependent Subspaces with Non-radially Symmetric and Skewed Densities
We extend the Gaussian scale mixture model of dependent subspace source densities to include non-radially symmetric densities using Generalized Gaussian random variables linked by ...
Jason A. Palmer, Kenneth Kreutz-Delgado, Bhaskar D...
ISIPTA
2005
IEEE
130views Mathematics» more  ISIPTA 2005»
15 years 8 months ago
Computing Lower and Upper Expectations under Epistemic Independence
This papers investigates the computation of lower/upper expectations that must cohere with a collection of probabilistic assessments and a collection of judgements of epistemic in...
Cassio Polpo de Campos, Fabio Gagliardi Cozman