Fetching the paper…
Reading the bibliography…
The goal of predictive sparse coding is to learn a representation of examples as sparse linear combinations of elements from a dictionary, such that a learned hypothesis linear in the new representation performs well on a predictive task.
The one-sided barrier problem for Gaussian noise
David Slepian · 1962
Earlier work this paper cites.
Uniform convergence of frequencies of occurence of events to their probabilities
Vladimir N. Vapnik and Alexey Ya. Chervonenkis · 1968
Earlier work this paper cites.
Stability of the solution of definite quadratic programs
James W. Daniel · 1973
Earlier work this paper cites.
On the method of bounded differences
Colin McDiarmid · 1989
Earlier work this paper cites.
Probability in Banach Spaces: isoperimetry and processes
Michel Ledoux and Michel Talagrand · 1991
Earlier work this paper cites.
Regression shrinkage and selection via the lasso
Robert Tibshirani · 1996
Earlier work this paper cites.
Gradient-based learning applied to document recognition
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner · 1998
Earlier work this paper cites.
Structural risk minimization over data-dependent hierarchies
John Shawe-Taylor, Peter L. Bartlett, Robert C. Williamson, and Martin Anthony · 1998
Earlier work this paper cites.
On the lasso and its dual
Michael R. Osborne, Brett Presnell, and Berwin A. Turlach · 2000
Earlier work this paper cites.
On the mathematical foundations of learning
Felipe Cucker and Steve Smale · 2002
Cited alongside, same era.
Matrix rank minimization with applications
Maryam Fazel · 2002
Cited alongside, same era.
Learning and Generalization with Applications to Neural Networks
Mathukumalli Vidyasagar · 2002
Cited alongside, same era.
Generalization error bounds for bayesian mixture algorithms
Ron Meir and Tong Zhang · 2003
Cited alongside, same era.
On the importance of small coordinate projections
Shahar Mendelson and Petra Philips · 2004
Cited alongside, same era.
Regularization and variable selection via the elastic net
Hui Zou and Trevor Hastie · 2005
Cited alongside, same era.
On the complexity of linear prediction: Risk bounds, margin bounds, and regularization
Sham M. Kakade, Karthik Sridharan, and Ambuj Tewari · 2009
Later among the works it cites.
Supervised dictionary learning
Julien Mairal, Francis Bach, Jean Ponce, Guillermo Sapiro, and Andrew Zisserman · 2009
Later among the works it cites.
Nonlinear learning using local coordinate coding
Kai Yu, Tong Zhang, and Yihong Gong · 2009
Later among the works it cites.
On the LASSO and Dantzig selector equivalence
M. Salman Asif and Justin Romberg · 2010
Later among the works it cites.
K-dimensional coding schemes in hilbert spaces
Andreas Maurer and Massimiliano Pontil · 2010
Later among the works it cites.
The sample complexity of dictionary learning
Daniel Vainsencher, Shie Mannor, and Alfred M. Bruckstein · 2011
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Support vector machines
Ingo Steinwart and Andreas Christmann · 2008
Cited alongside, same era.
Differentiable sparse coding
David M. Bradley and J. Andrew Bagnell · 2009
Cited alongside, same era.
Task-driven dictionary learning
Julien Mairal, Francis Bach, and Jean Ponce · 2012
Closest in time.
On the sample complexity of predictive sparse coding
Nishant A. Mehta and Alexander G. Gray · 2012
Closest in time.