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Coherent uncertainty quantification is a key strength of Bayesian methods.
An algorithm for quadratic programming
Frank, Marguerite and Wolfe, Philip · 1956
Earlier work this paper cites.
Some comments on Wolfe’s ‘away step’
Guélat, Jacques and Marcotte, Patrice · 1986
Earlier work this paper cites.
Orthogonal least squares methods and their application to non-linear system identification
Chen, Sheng, Billings, Stephen, and Luo, Wan · 1989
Earlier work this paper cites.
Matching pursuits with time-frequency dictionaries
Mallat, Stéphane and Zhang, Zhifeng · 1993
Earlier work this paper cites.
Regression shrinkage and selection via the lasso
Tibshirani, Robert · 1996
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Freund, Yoav and Schapire, Robert · 1997
Earlier work this paper cites.
Atomic decomposition by basis pursuit
Chen, Scott, Donoho, David, and Saunders, Michael · 1999
Earlier work this paper cites.
An introduction to variational methods for graphical models
Jordan, Michael, Ghahramani, Zoubin, Jaakkola, Tommi, and Saul, Lawrence · 1999
Earlier work this paper cites.
Monte Carlo Statistical Methods
Robert, Christian and Casella, George · 2004
Earlier work this paper cites.
Greed is good: algorithmic results for sparse approximation
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Black box variational inference
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A survey of compressed sensing
Boche, Holger, Calderbank, Robert, Kutyniok, Gitta, and Vybíral, Jan · 2015
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Streaming, distributed variational inference for Bayesian nonparametrics
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Variational inference via
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