Fetching the paper…
Reading the bibliography…
We present a new framework for deriving bounds on the generalization bound of statistical learning algorithms from the perspective of online learning.
Uniformly convex spaces
J. A. Clarkson · 1936
Earlier work this paper cites.
Limit distributions for sums of independent random variables
B. V. Gnedenko and A. N. Kolmogorov · 1954
Earlier work this paper cites.
On measures of entropy and information
A. Rényi · 1961
Earlier work this paper cites.
Eine informationstheoretische ungleichung und ihre anwendung auf den beweis der ergodizität von markoffschen ketten
I. Csiszár · 1963
Earlier work this paper cites.
On the Shannon capacity of an arbitrary channel
J. Kemperman · 1974
Earlier work this paper cites.
Probabilistic computations: Toward a unified measure of complexity
A. C. Yao · 1977
Earlier work this paper cites.
Distribution-free inequalities for the deleted and holdout error estimates
L. Devroye and T. J. Wagner · 1979
Earlier work this paper cites.
Theory of Pattern Recognition
V. Vapnik and A. Chervonenkis · 1979
Earlier work this paper cites.
A course on empirical processes
R. M. Dudley · 1984
Earlier work this paper cites.
Aggregating strategies
V. Vovk · 1990
Earlier work this paper cites.
Sharp uniform convexity and smoothness inequalities for trace norms
K. Ball, E. A. Carlen, and E. H. Lieb · 1994
Earlier work this paper cites.
The weighted majority algorithm
N. Littlestone and M. Warmuth · 1994
Earlier work this paper cites.
A decision-theoretic generalization of on-line learning and an application to boosting
Y. Freund and R. E. Schapire · 1997
Earlier work this paper cites.
A PAC analysis of a Bayesian estimator
J. Shawe-Taylor and R. C. Williamson · 1997
Earlier work this paper cites.
Covering number bounds of certain regularized linear function classes
T. Zhang · 1997
Earlier work this paper cites.
The sample complexity of pattern classification with neural networks: the size of the weights is more important than the size of the network
P. L. Bartlett · 1998
Earlier work this paper cites.
Some PAC-Bayesian theorems
D. A. McAllester · 1998
Earlier work this paper cites.
Entropy numbers of linear function classes
R. C. Williamson, A. J. Smola, and B. Schölkopf · 2000
Earlier work this paper cites.
Rademacher penalties and structural risk minimization
V. Koltchinskii · 2001
Earlier work this paper cites.
(not) bounding the true error
J. Langford and R. Caruana · 2001
Earlier work this paper cites.
Probability and finance: it’s only a game! , volume 491
G. Shafer and V. Vovk · 2001
Earlier work this paper cites.
Rademacher and Gaussian complexities: risk bounds and structural results
P. Bartlett and S. Mendelson · 2002
Earlier work this paper cites.
Model selection and error estimation
P. Bartlett, S. Boucheron, and G. Lugosi · 2002
Earlier work this paper cites.
Stability and generalization
O. Bousquet and A. Elisseeff · 2002
Earlier work this paper cites.
Topics in optimal transportation , volume 58
C. Villani · 2003
Earlier work this paper cites.
PAC-Bayesian statistical learning theory
J.-Y. Audibert · 2004
Earlier work this paper cites.
On the generalization ability of on-line learning algorithms
N. Cesa-Bianchi, A. Conconi, and C. Gentile · 2004
Earlier work this paper cites.
Empirical minimization
P. Bartlett and S. Mendelson · 2006
Earlier work this paper cites.
Prediction, Learning, and Games
N. Cesa-Bianchi and G. Lugosi · 2006
Cited alongside, same era.
Learning theory: stability is sufficient for generalization and necessary and sufficient for consistency of empirical risk minimization
S. Mukherjee, P. Niyogi, T. Poggio, and R. Rifkin · 2006
Cited alongside, same era.
PAC-Bayesian supervised classification
O. Catoni · 2007
Cited alongside, same era.
Improved second-order bounds for prediction with expert advice
N. Cesa-Bianchi, Y. Mansour, and G. Stoltz · 2007
Cited alongside, same era.
On the complexity of linear prediction: Risk bounds, margin bounds, and regularization
S. M. Kakade, K. Sridharan, and A. Tewari · 2008
Cited alongside, same era.
Lecture notes on online learning
A. Rakhlin · 2009
Cited alongside, same era.
Computing nonvacuous generalization bounds for deep (stochastic) neural networks with many more parameters than training data
G. K. Dziugaite and D. M. Roy · 2017
Later among the works it cites.
Zigzag: A new approach to adaptive online learning
D. J. Foster, A. Rakhlin, and K. Sridharan · 2017
Later among the works it cites.
Exploring generalization in deep learning
B. Neyshabur, S. Bhojanapalli, D. McAllester, and N. Srebro · 2017
Later among the works it cites.
On equivalence of martingale tail bounds and deterministic regret inequalities
A. Rakhlin and K. Sridharan · 2017
Later among the works it cites.
Information-theoretic analysis of generalization capability of learning algorithms
A. Xu and M. Raginsky · 2017
Later among the works it cites.
Simpler PAC-Bayesian bounds for hostile data
P. Alquier and B. Guedj · 2018
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Prediction with advice of unknown number of experts
A. Chernov and V. Vovk · 2010
Cited alongside, same era.
Learnability, stability and uniform convergence
S. Shalev-Shwartz, O. Shamir, N. Srebro, and K. Sridharan · 2010
Cited alongside, same era.
Differentially private empirical risk minimization
K. Chaudhuri, C. Monteleoni, and A. D. Sarwate · 2011
Cited alongside, same era.
On Rényi and Tsallis entropies and divergences for exponential families
F. Nielsen and R. Nock · 2011
Cited alongside, same era.
PAC-Bayesian inequalities for martingales
Y. Seldin, F. Laviolette, N. Cesa-Bianchi, J. Shawe-Taylor, and P. Auer · 2012
Cited alongside, same era.
Online learning and online convex optimization
S. Shalev-Shwartz · 2012
Cited alongside, same era.
Later among the works it cites.
Online learning: Sufficient statistics and the Burkholder method
D. J. Foster, A. Rakhlin, and K. Sridharan · 2018
Later among the works it cites.
A pac-bayesian approach to spectrally-normalized margin bounds for neural networks
B. Neyshabur, S. Bhojanapalli, and N. Srebro · 2018
Later among the works it cites.
The many faces of exponential weights in online learning
D. van der Hoeven, T. van Erven, and W. Kotłowski · 2018
Later among the works it cites.
An optimal transport view on generalization
J. Zhang, T. Liu, and D. Tao · 2018
Later among the works it cites.
PAC-Bayes un-expected Bernstein inequality
Z. Mhammedi, P. Grünwald, and B. Guedj · 2019
Later among the works it cites.
Uniform convergence may be unable to explain generalization in deep learning
V. Nagarajan and J. Z. Kolter · 2019
Later among the works it cites.
A modern introduction to online learning
F. Orabona · 2019
Later among the works it cites.
How much does your data exploration overfit? controlling bias via information usage
D. Russo and J. Zou · 2019
Later among the works it cites.
An information-theoretic view of generalization via Wasserstein distance
H. Wang, M. Diaz, J. C. S. Santos Filho, and F. P. Calmon · 2019
Later among the works it cites.
Generalization bounds via information density and conditional information density
F. Hellström and G. Durisi · 2020
Later among the works it cites.
Fantastic generalization measures and where to find them
Y. Jiang, B. Neyshabur, H. Mobahi, D. Krishnan, and S. Bengio · 2020
Later among the works it cites.
A limitation of the PAC-Bayes framework
R. Livni and S. Moran · 2020
Later among the works it cites.
Reasoning about generalization via conditional mutual information
T. Steinke and L. Zakynthinou · 2020
Later among the works it cites.
Estimating means of bounded random variables by betting
I. Waudby-Smith and A. Ramdas · 2020
Later among the works it cites.
Non-exponentially weighted aggregation: regret bounds for unbounded loss functions
P. Alquier · 2021
Later among the works it cites.
PAC-Bayes, MAC-Bayes and conditional mutual information: Fast rate bounds that handle general VC classes
P. Grünwald, T. Steinke, and L. Zakynthinou · 2021
Later among the works it cites.
Towards a unified information-theoretic framework for generalization
M. Haghifam, G. K. Dziugaite, S. Moran, and D. Roy · 2021
Later among the works it cites.
Information-theoretic generalization bounds for stochastic gradient descent
G. Neu, G. K. Dziugaite, M. Haghifam, and D. M. Roy · 2021
Later among the works it cites.
Tight concentrations and confidence sequences from the regret of universal portfolio
F. Orabona and K.-S. Jun · 2021
Later among the works it cites.
Tighter expected generalization error bounds via Wasserstein distance
B. Rodríguez-Gálvez, G. Bassi, R. Thobaben, and M. Skoglund · 2021
Later among the works it cites.
Generalization bounds via convex analysis
G. Lugosi and G. Neu · 2022
Later among the works it cites.