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» Bayesian Inference for Sparse Generalized Linear Models
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CLADE
2008
IEEE
15 years 8 months ago
SWARM: a scientific workflow for supporting bayesian approaches to improve metabolic models
With the exponential growth of complete genome sequences, the analysis of these sequences is becoming a powerful approach to build genome-scale metabolic models. These models can ...
Xinghua Shi, Rick Stevens
NIPS
2001
15 years 3 months ago
Bayesian Predictive Profiles With Applications to Retail Transaction Data
Massive transaction data sets are recorded in a routine manner in telecommunications, retail commerce, and Web site management. In this paper we address the problem of inferring p...
Igor V. Cadez, Padhraic Smyth
108
Voted
JMLR
2010
93views more  JMLR 2010»
14 years 8 months ago
Distinguishing between cause and effect
We propose a novel method for inferring whether X causes Y or vice versa from joint observations of X and Y . The basic idea is to model the observed data using probabilistic late...
Joris M. Mooij, Dominik Janzing
CORR
2012
Springer
218views Education» more  CORR 2012»
13 years 9 months ago
Robust 1-bit compressed sensing and sparse logistic regression: A convex programming approach
This paper develops theoretical results regarding noisy 1-bit compressed sensing and sparse binomial regression. We demonstrate that a single convex program gives an accurate estim...
Yaniv Plan, Roman Vershynin
CORR
2010
Springer
127views Education» more  CORR 2010»
15 years 13 days ago
Learning Networks of Stochastic Differential Equations
We consider linear models for stochastic dynamics. To any such model can be associated a network (namely a directed graph) describing which degrees of freedom interact under the d...
José Bento, Morteza Ibrahimi, Andrea Montan...