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» A maximum likelihood framework for protein design
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TCBB
2008
108views more  TCBB 2008»
13 years 4 months ago
Statistical Characterization of Protein Ensembles
When accounting for structural fluctuations or measurement errors, a single rigid structure may not be sufficient to represent a protein. One approach to solve this problem is to r...
Diego Rother, Guillermo Sapiro, Vijay Pande
TIT
2010
170views Education» more  TIT 2010»
13 years 20 hour ago
Belief propagation estimation of protein and domain interactions using the sum-product algorithm
We present a novel framework to estimate protein-protein (PPI) and domain-domain (DDI) interactions based on a belief propagation estimation method that efficiently computes inter...
Faruck Morcos, Marcin Sikora, Mark S. Alber, Dale ...
GLOBECOM
2009
IEEE
13 years 9 months ago
A Framework of Multiplicative Spread Spectrum Embedding for Data Hiding: Performance, Decoder and Signature Design
In this paper, we have investigated several aspects of multiplicative spread spectrum (MSS) embedding for Data Hiding. First, we analyze the probability of error of the maximum lik...
Amir Valizadeh, Z. Jane Wang
JMLR
2008
83views more  JMLR 2008»
13 years 5 months ago
Evidence Contrary to the Statistical View of Boosting
The statistical perspective on boosting algorithms focuses on optimization, drawing parallels with maximum likelihood estimation for logistic regression. In this paper we present ...
David Mease, Abraham Wyner
JMLR
2008
209views more  JMLR 2008»
13 years 5 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger