Fetching the paper…
Reading the bibliography…
We study learning problems involving arbitrary classes of functions $F$, distributions $X$ and targets $Y$.
Some limit theorems for empirical processes
Evarist Giné and Joel Zinn · 1984
Earlier work this paper cites.
Probability in Banach Space
M. Ledoux and M. Talagrand · 1991
Earlier work this paper cites.
Domination inequality for martingale transforms of a Rademacher sequence
PawełHitczenko · 1993
Earlier work this paper cites.
Sharper bounds for Gaussian and empirical processes
M. Talagrand · 1994
Earlier work this paper cites.
A probabilistic theory of pattern recognition
L. Devroye, L. Györfi, and G. Lugosi · 1996
Earlier work this paper cites.
Weak convergence and empirical processes
A.W. van der Vaart and J.A. Wellner · 1996
Earlier work this paper cites.
Neural network learning: theoretical foundations
M. Anthony and P. L. Bartlett · 1999
Earlier work this paper cites.
Introduction to nonparametric estimation
A. B. Tsybakov · 2004
Earlier work this paper cites.
Localized Rademacher complexities
P.L. Bartlett, O. Bousquet, and S. Mendelson · 2005
Earlier work this paper cites.
Proof of the optimality of the empirical star algorithm
J.-Y. Audibert · 2007
Cited alongside, same era.
Learning by mirror averaging
A. Juditsky, P. Rigollet, and A. B. Tsybakov · 2008
Cited alongside, same era.
Oracle inequalities in empirical risk minimization and sparse recovery problems
V. Koltchinskii · 2008
Cited alongside, same era.
Obtaining fast error rates in nonconvex situations
Shahar Mendelson · 2008
Cited alongside, same era.
Fast learning rates in statistical inference through aggregation
Jean-Yves Audibert · 2009
Cited alongside, same era.
Aggregation via empirical risk minimization
Guillaume Lecué and Shahar Mendelson · 2009
Cited alongside, same era.
Learning without concentration
S. Mendelson · 2015
Later among the works it cites.
Local vs. global parameters – breaking the Gaussian complexity barrier
S. Mendelson · 2015
Later among the works it cites.
Upper bounds on product and multiplier empirical processes
Shahar Mendelson · 2016
Later among the works it cites.
Learning subgaussian classes: Upper and minimax bounds
G. Lecué and S. Mendelson · 2017
Closest in time.
Extending the scope of the small-ball method
S. Mendelson · 2017
Closest in time.
Learning without concentration for general loss functions
Shahar Mendelson · 2017
Closest in time.
On aggregation for heavy-tailed classes
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
S. Boucheron, G. Lugosi, and P. Massart · 2013
Cited alongside, same era.
Sudakov-type minoration for log-concave vectors
Rafał Latała · 2014
Cited alongside, same era.
Learning with square loss: Localization through offset rademacher complexity
Tengyuan Liang, Alexander Rakhlin, and Karthik Sridharan · 2015
Cited alongside, same era.
Risk minimization by median-of-means tournaments
G. Lugosi and S. Mendelson
Cited in the paper.
Shahar Mendelson · 2017
Closest in time.
Empirical entropy, minimax regret and minimax risk
Alexander Rakhlin, Karthik Sridharan, and Alexandre B. Tsybakov · 2017
Closest in time.